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Image Analysis and Processing - ICIAP 2023 Workshops [[electronic resource] ] : Udine, Italy, September 11–15, 2023, Proceedings, Part II / / edited by Gian Luca Foresti, Andrea Fusiello, Edwin Hancock
Image Analysis and Processing - ICIAP 2023 Workshops [[electronic resource] ] : Udine, Italy, September 11–15, 2023, Proceedings, Part II / / edited by Gian Luca Foresti, Andrea Fusiello, Edwin Hancock
Autore Foresti Gian Luca
Edizione [1st ed. 2024.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Descrizione fisica 1 online resource (514 pages)
Disciplina 006.37
Altri autori (Persone) FusielloAndrea
HancockEdwin
Collana Lecture Notes in Computer Science
Soggetto topico Computer vision
Computer engineering
Computer networks
Machine learning
Education - Data processing
Pattern recognition systems
Computer Vision
Computer Engineering and Networks
Machine Learning
Computers and Education
Automated Pattern Recognition
ISBN 3-031-51026-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents - Part II -- Contents - Part I -- Artificial Intelligence and Radiomics in Computer-Aided Diagnosis (AIRCAD) -- Leukocytes Classification Methods: Effectiveness and Robustness in a Real Application Scenario -- 1 Introduction -- 2 Materials and Methods -- 2.1 Data Sets -- 2.2 Data Pre-processing -- 2.3 Methods -- 3 Experimental Evaluation -- 3.1 Experimental Setup -- 3.2 Experimental Results -- 4 Conclusions -- References -- Vision Transformers for Breast Cancer Histology Image Classification -- 1 Introduction -- 2 Background and Related Work -- 2.1 Deep Learning in Histopathology Images of Breast Cancer -- 2.2 Vision Transformers -- 2.3 BACH: Grand Challenge on Breast Cancer Histology Images -- 3 Methodology -- 4 Experimental Evaluation -- 5 Discussion and Conclusion -- References -- Editable Stain Transformation of Histological Images Using Unpaired GANs -- 1 Introduction -- 2 Related Work -- 2.1 Overview of xAI-CycleGAN -- 2.2 SeFa Algorithm for Editable Outputs -- 2.3 cCGAN for Stain Transformation -- 3 Methods -- 3.1 Dataset -- 3.2 Separating Structure from Style -- 3.3 Editable Generation Results Using SeFa -- 4 Results -- 5 Discussion -- 6 Future Work -- References -- Assessing the Robustness and Reproducibility of CT Radiomics Features in Non-small-cell Lung Carcinoma -- 1 Introduction -- 2 Materials and Methods -- 2.1 Dataset -- 2.2 Segmentation -- 2.3 Image Pre-processing and Feature Extraction -- 2.4 Statistical Analysis -- 2.5 Feature Reduction, Selection, and Machine Learning -- 3 Results -- 3.1 Statistical Analysis -- 3.2 Feature Reduction, Selection, and Machine Learning -- 4 Discussion and Conclusions -- References -- Prediction of High Pathological Grade in Prostate Cancer Patients Undergoing [18F]-PSMA PET/CT: A Preliminary Radiomics Study -- 1 Introduction -- 2 Materials and Methods.
2.1 PET/CT Imaging -- 2.2 Inclusion Criteria -- 2.3 The Gleason Score -- 2.4 Radiomics Analysis -- 3 Results -- 4 Discussions and Conclusion -- References -- MTANet: Multi-Type Attention Ensemble for Malaria Parasite Detection -- 1 Introduction -- 2 Related Work -- 3 Materials and Methods -- 3.1 Dataset -- 3.2 YOLO Detectors and YOLOv5 -- 3.3 Convolutional Block Attention Module (CBAM) -- 3.4 Our Proposed Method: MTANet -- 3.5 Metrics -- 4 Experimental Results and Discussion -- 4.1 Experimental Setup -- 4.2 Experimental Results -- 5 Conclusions -- References -- Breast Mass Detection and Classification Using Transfer Learning on OPTIMAM Dataset Through RadImageNet Weights -- 1 Introduction -- 2 Methods -- 2.1 Dataset -- 2.2 Proposed Method -- 2.3 YOLO -- 3 Results -- 3.1 Breast Mass Detection -- 3.2 Breast Mass Classification -- 4 Discussion -- 5 Conclusion -- References -- Prostate Cancer Detection: Performance of Radiomics Analysis in Multiparametric MRI -- 1 Introduction -- 2 Materials and Methods -- 2.1 Population -- 2.2 MRI Technique -- 2.3 Manual Segmentation -- 2.4 Radiomics Features Extraction -- 2.5 Computational and Statistical Analyses -- 3 Results -- 3.1 Population -- 3.2 Performance of Radiomics -- 4 Discussion -- 5 Conclusion -- References -- Grading and Staging of Bladder Tumors Using Radiomics Analysis in Magnetic Resonance Imaging -- 1 Introduction -- 2 Materials and Methods -- 2.1 Population -- 2.2 MRI Technique -- 2.3 Qualitative Imaging Analysis -- 2.4 Segmentation and Radiomics Features Extraction -- 2.5 Computational and Statistical Analyses -- 3 Results -- 3.1 Population -- 3.2 Performance of Radiomics -- 4 Discussion -- 5 Conclusion -- References -- Combined Data Augmentation for HEp-2 Cells Image Classification -- 1 Introduction -- 2 Materials and Method -- 2.1 Dataset -- 2.2 Basic Image Manipulation -- 2.3 CVAE.
2.4 Experimental Protocol -- 3 Results -- 4 Conclusions -- References -- Multi-modal Medical Imaging Processing (M3IP) -- Harnessing Multi-modality and Expert Knowledge for Adverse Events Prediction in Clinical Notes -- 1 Introduction -- 2 Adverse Events Prediction: Task Formulation -- 3 Data and Information Extraction -- 3.1 Features of Interest -- 3.2 Features Extraction from Structured Data -- 3.3 Features Extraction from Unstructured Data -- 3.4 Multi-modality: Early and Late Fusion -- 4 Training -- 4.1 Datasets and Metrics -- 4.2 Classification Suite -- 4.3 Imbalance Learning -- 5 Results -- 6 Conclusion and Future Work -- References -- A Multimodal Deep Learning Based Approach for Alzheimer's Disease Diagnosis -- 1 Introduction -- 2 Materials and Methods -- 2.1 The Population -- 2.2 Data Preprocessing -- 2.3 The Neural Network -- 2.4 The Proposed Multimodal Approach -- 3 Experimental Set-Up -- 4 Results -- 5 Conclusion -- References -- A Systematic Review of Multimodal Deep Learning Approaches for COVID-19 Diagnosis -- 1 Introduction -- 2 Existing Literature Reviews -- 3 Materials and Methods -- 3.1 Data Sources -- 3.2 Search Strategy and Related Articles -- 4 Results and Discussion -- 5 Conclusions -- References -- A Multi-dimensional Joint ICA Model with Gaussian Copula -- 1 Introduction -- 2 Dataset -- 3 Methods -- 3.1 Conventional Joint ICA -- 3.2 Joint ICA with Different Variances -- 3.3 Proposed Copula Joint ICA -- 4 Implementation -- 4.1 Simulation -- 5 Results -- 6 Conclusion -- References -- Federated Learning in Medical Imaging and Vision (FEDMED) -- Federated Learning for Data and Model Heterogeneity in Medical Imaging -- 1 Introduction -- 2 Related Work -- 2.1 Federated Learning -- 2.2 Model and Data Heterogeneity -- 3 Federated Learning with Heterogeneous Data and Models -- 3.1 Model Heterogeneity.
3.2 Data and Labels Heterogeneity -- 4 Experimental Results -- 4.1 Datasets and Models -- 4.2 Comparison with State-of-the-Art Methods -- 5 Conclusion -- References -- Experience Sharing and Human-in-the-Loop Optimization for Federated Robot Navigation Recommendation -- 1 Introduction -- 2 Learning from Experience -- 3 Recommendation as the Silver Bullet -- 4 Human-in-the-Loop Optimization -- 5 Security-Related Considerations -- 6 Conclusion -- References -- FeDETR: A Federated Approach for Stenosis Detection in Coronary Angiography -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Problem Formulation -- 4 Experimental Evaluation -- 4.1 Dataset -- 4.2 Training Procedure -- 4.3 Results -- 5 Conclusion -- References -- FeDZIO: Decentralized Federated Knowledge Distillation on Edge Devices -- 1 Introduction -- 2 Related Work -- 3 Method -- 4 Performance Evaluation -- 4.1 Dataset -- 4.2 Training Procedure -- 4.3 Experimental Results -- 5 Conclusions -- References -- A Federated Learning Framework for Stenosis Detection -- 1 Introduction -- 2 Material and Methods -- 2.1 Datasets -- 2.2 Experimental Protocol -- 3 Results and Discussion -- 4 Conclusion -- References -- Benchmarking Federated Learning Frameworks for Medical Imaging Tasks -- 1 Introduction -- 2 Related Works -- 3 Experiments -- 4 Results -- 5 Conclusions -- 6 Future Works -- References -- Artificial Intelligence for Digital Humanities (AI4DH) -- Examining the Robustness of an Ensemble Learning Model for Credibility Based Fake News Detection -- 1 Introduction -- 2 Related Works -- 2.1 The Liar Dataset -- 2.2 The FakeNewsNet Dataset -- 2.3 The Fake and Real News Dataset -- 2.4 Spawned Dataset -- 3 Methods -- 3.1 Two-Class Boosted Decision Tree (BDT) -- 3.2 Two Class Neural Network -- 3.3 Mixture of Experts -- 3.4 Two Class Logistic Regression -- 4 Experimental Results.
4.1 Experiments Where the Train and Test Set are the Same -- 4.2 Experiments Where the Train and Test Set are Different -- 5 Conclusion -- References -- Prompt Me a Dataset: An Investigation of Text-Image Prompting for Historical Image Dataset Creation Using Foundation Models -- 1 Introduction -- 2 Current State of the Research -- 3 Pipeline -- 4 Text-Image Prompt Evaluation -- 4.1 A Note on the Environment -- 5 Conclusion -- References -- Artificial Intelligence in Art Generation: An Open Issue -- 1 Introduction -- 2 State of the Art -- 3 The Experts' Point of View -- 3.1 The Philosopher's Point of View -- 3.2 The Art Historian's Point of View -- 3.3 The Computer Scientist's Point of View -- 4 Experimental Results -- 4.1 The Art Exhibition -- 4.2 Users' Feedbacks -- 5 Conclusions -- References -- A Deep Learning Approach for Painting Retrieval Based on Genre Similarity -- 1 Introduction -- 2 Methodology and Experiments -- 2.1 Convolutional Neural Network -- 2.2 Dataset -- 2.3 Nearest Neighbour Algorithm and Similarity Measure -- 2.4 Experiments -- 3 Results -- 3.1 Classifier Performance -- 3.2 Comparison of CBIR Performance Before and After Fine-Tuning with Specific Domain Knowledge -- 3.3 Parameters Optimization of the Approximate Nearest Neighbour Algorithm -- 3.4 Introducing SimArt: A Web Application for Efficiently Searching Similar Artworks -- 4 Discussion and Conclusions -- References -- GeomEthics: Ethical Considerations About Using Artificial Intelligence in Geomatics -- 1 Introduction -- 2 The Use of Artificial Intelligence in Geomatics -- 3 Ethics of Artificial Intelligence in Geomatics -- 3.1 Geospatial Data Fairness -- 3.2 Local Identity -- 3.3 Geo-Privacy -- 4 Conclusions and Future Works -- References -- Fine Art Pattern Extraction and Recognition (FAPER).
Enhancing Preservation and Restoration of Open Reel Audio Tapes Through Computer Vision.
Record Nr. UNINA-9910805575203321
Foresti Gian Luca  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Image Analysis and Processing - ICIAP 2023 Workshops [[electronic resource] ] : Udine, Italy, September 11–15, 2023, Proceedings, Part I / / edited by Gian Luca Foresti, Andrea Fusiello, Edwin Hancock
Image Analysis and Processing - ICIAP 2023 Workshops [[electronic resource] ] : Udine, Italy, September 11–15, 2023, Proceedings, Part I / / edited by Gian Luca Foresti, Andrea Fusiello, Edwin Hancock
Autore Foresti Gian Luca
Edizione [1st ed. 2024.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Descrizione fisica 1 online resource (519 pages)
Disciplina 006.37
Altri autori (Persone) FusielloAndrea
HancockEdwin
Collana Lecture Notes in Computer Science
Soggetto topico Computer vision
Computer engineering
Computer networks
Machine learning
Education - Data processing
Pattern recognition systems
Computer Vision
Computer Engineering and Networks
Machine Learning
Computers and Education
Automated Pattern Recognition
ISBN 3-031-51023-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents - Part I -- Contents - Part II -- Industrial Poster Session -- Instance Segmentation Applied to Underground Infrastructures -- 1 Introduction -- 2 Pipes Recognition -- 2.1 Dataset Creation -- 2.2 Dataset Description -- 2.3 Deep Learning Architecture -- 2.4 Classification Overhead -- 3 Experiments -- 3.1 Training -- 3.2 Instance Segmentation Results -- 3.3 Classification Refinement Results -- 4 Conclusion -- References -- Generating Invariance-Based Adversarial Examples: Bringing Humans Back into the Loop -- 1 Introduction -- 2 Adversarial Examples -- 2.1 Sensitivity-Based Adversarial Examples -- 2.2 Invariance-Based Adversarial Examples -- 3 Human Perception -- 4 Experiments -- 4.1 Stimuli -- 4.2 Human Subjects -- 4.3 Eye Tracking Experimental Set-Up -- 4.4 Creation of Occlusion-Based Adversarial Examples -- 5 Results -- 6 Adaptive Approaches -- 7 Conclusion -- References -- MARS: Mask Attention Refinement with Sequential Quadtree Nodes for Car Damage Instance Segmentation -- 1 Introduction -- 2 Related Works -- 3 Proposed Method -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Comparison with SOTA -- 4.3 Implementation Details -- 5 Conclusions -- References -- On-Device Learning with Binary Neural Networks -- 1 Introduction -- 2 Related Literature -- 2.1 Continual Learning -- 2.2 Binary Neural Networks -- 3 On-Device CWR Optimization -- 3.1 Gradients Computation -- 3.2 Quantization Strategy -- 4 Experiments -- 5 Conclusion -- References -- Towards One-Shot PCB Component Detection with YOLO -- 1 Introduction -- 2 Background -- 3 Methodology -- 3.1 Dataset Generation -- 3.2 Improving YOLOv5 Architecture for Small Object Detection -- 3.3 Training Procedure and Evaluation Metrics -- 4 Experimental Results -- 4.1 Experiments with Original YOLOv5 -- 4.2 Experiments with Improved YOLOv5 -- 5 Conclusion.
References -- Wildfires Classification: A Comparative Study -- 1 Introduction -- 2 Datasets for Fire and Smoke Analysis -- 3 Fire Analysis Techniques -- 4 Wildfires Classification -- 4.1 Selected Deep Models -- 4.2 Wildfires Dataset -- 4.3 Deploying the Model on Embedded Systems -- 5 Experimental Results -- 5.1 Results on the FireNet Dataset -- 5.2 Results on Our Wildfires Dataset -- 6 Conclusions and Future Works -- References -- A General Purpose Method for Image Collection Summarization and Exploration -- 1 Introduction and Background -- 2 Proposed Method -- 2.1 Group Selection -- 2.2 Clustering of Pictures Within a Group -- 2.3 Best Picture Selection -- 3 Datasets -- 3.1 Automatic Triage for a Photo Series -- 3.2 Camera Scene Detection Dataset -- 4 Experimental Setup -- 4.1 Data Setup -- 4.2 Evaluation Metrics -- 4.3 Experimental Details -- 5 Results -- 5.1 Subjective Results -- 6 Conclusions -- References -- Automated Identification of Failure Cases in Organ at Risk Segmentation Using Distance Metrics: A Study on CT Data -- 1 Introduction -- 2 Methods and Materials -- 2.1 Dice and Hausdorff Distance Metrics -- 2.2 Dataset -- 2.3 Model Architecture -- 2.4 Experimental Setup -- 3 Results and Discussion -- 4 Conclusion -- References -- Digitizer: A Synthetic Dataset for Well-Log Analysis -- 1 Introduction -- 2 Generating Synthetic Well-Log Curves -- 3 Dataset Analysis -- 4 Conclusions -- References -- CNN-BLSTM Model for Arabic Text Recognition in Unconstrained Captured Identity Documents -- 1 Introduction -- 2 Related Works -- 3 Problem Statement -- 3.1 Identity Document Reading -- 3.2 Arabic Text Recognition -- 4 Proposed Method -- 4.1 Architecture Description -- 4.2 Training Parameters -- 4.3 Data Pre-processing -- 5 Experiments -- 5.1 Dataset -- 5.2 Evaluation Metrics -- 5.3 Model Training -- 5.4 Model Evaluation -- 6 Conclusion -- References.
Advances in Gaze Analysis, Visual attention and Eye-gaze modelling (AGAVE) -- Detection and Localization of Changes in Immersive Virtual Reality -- 1 Introduction -- 2 Experiment and Computational Model -- 2.1 Task -- 2.2 Measures -- 2.3 Apparatus and Procedure -- 2.4 Participants -- 2.5 Computational Model -- 3 Results -- 3.1 Change Localization Experiment -- 3.2 The Proposed Model Accounts for the Patterns of Human Data -- 4 Discussion and Conclusion -- References -- Pain and Fear in the Eyes: Gaze Dynamics Predicts Social Anxiety from Fear Generalisation -- 1 Introduction -- 2 Background and Hypotheses -- 3 Method -- 3.1 Participants and Procedure -- 3.2 Proposed Model and Data Analyses -- 4 Results -- 5 Conclusions -- References -- Eye Gaze Analysis Towards an AI System for Dynamic Content Layout -- 1 Introduction -- 2 AI System -- 3 Experiment -- 3.1 Overview -- 3.2 Set-Up -- 3.3 Clips -- 3.4 Data Analysis -- 4 Results -- 4.1 Graphic Durations -- 4.2 Fixation Durations -- 4.3 Fixation Scores -- 4.4 Region of Interest Hypothesis -- 5 Discussion -- 5.1 Target 1 -- 5.2 Target 2 -- 5.3 Targets 3 and 4 -- 5.4 Target 5 -- 5.5 Target 6 -- 6 Conclusions -- References -- Beyond Vision: Physics Meets AI (BVPAI) -- A Variational AutoEncoder for Model Independent Searches of New Physics at LHC -- 1 Introduction -- 2 The Physics Use-Case: An Effective Field Theory Interpretation of Vector Boson Scattering -- 2.1 Same Sign WW Scattering -- 2.2 Modeling the Anomalies: The SM as an Effective Field Theory -- 3 Variational AutoEncoders -- 3.1 The VAE Architecture -- 3.2 Anomaly Detection with VAEs -- 4 Embedding a Classification Step in the Training to Optimize for Discrimination -- 4.1 Results -- 5 Conclusions and Future Perspectives -- References -- Adaptive Voronoi Binning in Muon Radiography for Detecting Subsurface Cavities.
1 Introduction to Muon Radiography -- 1.1 Cosmic Rays -- 1.2 Muon Radiography -- 2 The MIMA Detector and Its Application at the Temperino Mine -- 3 Adaptive Tessellation Through Voronoi Binning -- 4 Conclusion -- References -- Optimizing Deep Learning Models for Cell Recognition in Fluorescence Microscopy: The Impact of Loss Functions on Performance and Generalization -- 1 Introduction -- 2 Related Works -- 3 Methods -- 3.1 Model Training -- 4 Results -- 5 Discussion -- References -- A New IBA Imaging System for the Transportable MACHINA Accelerator -- 1 Introduction -- 2 Methods -- 3 Tests and Results -- 4 Conclusions -- References -- Abstracts Embeddings Evaluation: A Case Study of Artificial Intelligence and Medical Imaging for the COVID-19 Infection -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Dataset -- 3.2 Label Assignment -- 3.3 Models -- 3.4 Performance Metrics -- 4 Results and Discussions -- 5 Conclusions -- References -- Pigments and Brush Strokes: Investigating the Painting Techniques Using MA-XRF and Laser Profilometry -- 1 Introduction -- 2 Materials and Methods -- 3 Results and Discussion -- 4 Conclusions -- References -- Automatic Affect Analysis and Synthesis (3AS) -- Pain Classification and Intensity Estimation Through the Analysis of Facial Action Units -- 1 Introduction -- 2 Background and Rationales -- 3 Materials and Methods -- 3.1 Datasets -- 3.2 Methods -- 3.3 Results -- 4 Conclusion -- References -- Towards a Better Understanding of Human Emotions: Challenges of Dataset Labeling -- 1 Introduction -- 2 Related Work -- 3 Proposed Emotion Taxonomy -- 4 Experiments -- 4.1 Relabeling the AffectNet Dataset -- 4.2 Results -- 5 Conclusions -- References -- Video-Based Emotion Estimation Using Deep Neural Networks: A Comparative Study -- 1 Introduction -- 2 Related Work -- 3 The OMG-Emotion Dataset.
4 The Video Emotion Estimation Pipeline -- 4.1 Pre-processing -- 4.2 Backbone -- 4.3 Temporal Aggregation -- 4.4 Multi-layer Perceptron -- 4.5 Loss Functions -- 5 Experiments and Results -- 5.1 Ablation Analysis -- 5.2 Model Comparison -- 5.3 State-of-the-Art Comparison -- 6 Conclusions -- A Appendix -- References -- International Contest on Fire Detection (ONFIRE) -- ONFIRE Contest 2023: Real-Time Fire Detection on the Edge -- 1 Introduction -- 2 Related Works -- 3 Contest Dataset and Task -- 4 Evaluation Metrics -- 5 Conclusion -- References -- FIRESTART: Fire Ignition Recognition with Enhanced Smoothing Techniques and Real-Time Tracking -- 1 Introduction -- 2 Materials and Methods -- 2.1 Dataset -- 2.2 Convolutional Neural Networks -- 2.3 Vision Transformers -- 2.4 The Proposed Approach -- 2.5 Metrics -- 3 Experimental Results and Discussion -- 3.1 Experimental Setup -- 3.2 Experimental Results -- 4 Conclusions -- References -- Rapid Fire Detection with Early Exiting -- 1 Introduction -- 2 Related Works -- 2.1 Fire Detection -- 2.2 Advantages of Deep Learning -- 2.3 Early Exiting -- 3 Methodology -- 3.1 Dataset -- 3.2 Model Architectures -- 4 Preliminary Results -- 5 Conclusions -- References -- Recent Advances in Digital Security: Biometrics and Forensics (BIOFORM) -- Morphing-Attacks Against Binary Fingervein Templates -- 1 Introduction -- 2 Morphing of Binary Finger Vein Templates -- 3 Experimental Settings -- 3.1 Assessment Criteria -- 3.2 Data and Recognition Software -- 4 Experimental Results -- 4.1 Threat Evaluation -- 4.2 Detecting Morphed Templates -- 5 Conclusion and Future Work -- References -- A Robust Approach for Crop Misalignment Estimation in Single and Double JPEG Compressed Images -- 1 Introduction -- 2 Proposed Approach -- 3 Experimental Results -- 4 Conclusions -- References.
Human-in-the-Loop Person Re-Identification as a Defence Against Adversarial Attacks.
Record Nr. UNINA-9910805576903321
Foresti Gian Luca  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Image Analysis and Processing - ICIAP 2023 Workshops [[electronic resource] ] : Udine, Italy, September 11–15, 2023, Proceedings, Part II / / edited by Gian Luca Foresti, Andrea Fusiello, Edwin Hancock
Image Analysis and Processing - ICIAP 2023 Workshops [[electronic resource] ] : Udine, Italy, September 11–15, 2023, Proceedings, Part II / / edited by Gian Luca Foresti, Andrea Fusiello, Edwin Hancock
Autore Foresti Gian Luca
Edizione [1st ed. 2024.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Descrizione fisica 1 online resource (514 pages)
Disciplina 006.37
Altri autori (Persone) FusielloAndrea
HancockEdwin
Collana Lecture Notes in Computer Science
Soggetto topico Computer vision
Computer engineering
Computer networks
Machine learning
Education - Data processing
Pattern recognition systems
Computer Vision
Computer Engineering and Networks
Machine Learning
Computers and Education
Automated Pattern Recognition
ISBN 3-031-51026-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents - Part II -- Contents - Part I -- Artificial Intelligence and Radiomics in Computer-Aided Diagnosis (AIRCAD) -- Leukocytes Classification Methods: Effectiveness and Robustness in a Real Application Scenario -- 1 Introduction -- 2 Materials and Methods -- 2.1 Data Sets -- 2.2 Data Pre-processing -- 2.3 Methods -- 3 Experimental Evaluation -- 3.1 Experimental Setup -- 3.2 Experimental Results -- 4 Conclusions -- References -- Vision Transformers for Breast Cancer Histology Image Classification -- 1 Introduction -- 2 Background and Related Work -- 2.1 Deep Learning in Histopathology Images of Breast Cancer -- 2.2 Vision Transformers -- 2.3 BACH: Grand Challenge on Breast Cancer Histology Images -- 3 Methodology -- 4 Experimental Evaluation -- 5 Discussion and Conclusion -- References -- Editable Stain Transformation of Histological Images Using Unpaired GANs -- 1 Introduction -- 2 Related Work -- 2.1 Overview of xAI-CycleGAN -- 2.2 SeFa Algorithm for Editable Outputs -- 2.3 cCGAN for Stain Transformation -- 3 Methods -- 3.1 Dataset -- 3.2 Separating Structure from Style -- 3.3 Editable Generation Results Using SeFa -- 4 Results -- 5 Discussion -- 6 Future Work -- References -- Assessing the Robustness and Reproducibility of CT Radiomics Features in Non-small-cell Lung Carcinoma -- 1 Introduction -- 2 Materials and Methods -- 2.1 Dataset -- 2.2 Segmentation -- 2.3 Image Pre-processing and Feature Extraction -- 2.4 Statistical Analysis -- 2.5 Feature Reduction, Selection, and Machine Learning -- 3 Results -- 3.1 Statistical Analysis -- 3.2 Feature Reduction, Selection, and Machine Learning -- 4 Discussion and Conclusions -- References -- Prediction of High Pathological Grade in Prostate Cancer Patients Undergoing [18F]-PSMA PET/CT: A Preliminary Radiomics Study -- 1 Introduction -- 2 Materials and Methods.
2.1 PET/CT Imaging -- 2.2 Inclusion Criteria -- 2.3 The Gleason Score -- 2.4 Radiomics Analysis -- 3 Results -- 4 Discussions and Conclusion -- References -- MTANet: Multi-Type Attention Ensemble for Malaria Parasite Detection -- 1 Introduction -- 2 Related Work -- 3 Materials and Methods -- 3.1 Dataset -- 3.2 YOLO Detectors and YOLOv5 -- 3.3 Convolutional Block Attention Module (CBAM) -- 3.4 Our Proposed Method: MTANet -- 3.5 Metrics -- 4 Experimental Results and Discussion -- 4.1 Experimental Setup -- 4.2 Experimental Results -- 5 Conclusions -- References -- Breast Mass Detection and Classification Using Transfer Learning on OPTIMAM Dataset Through RadImageNet Weights -- 1 Introduction -- 2 Methods -- 2.1 Dataset -- 2.2 Proposed Method -- 2.3 YOLO -- 3 Results -- 3.1 Breast Mass Detection -- 3.2 Breast Mass Classification -- 4 Discussion -- 5 Conclusion -- References -- Prostate Cancer Detection: Performance of Radiomics Analysis in Multiparametric MRI -- 1 Introduction -- 2 Materials and Methods -- 2.1 Population -- 2.2 MRI Technique -- 2.3 Manual Segmentation -- 2.4 Radiomics Features Extraction -- 2.5 Computational and Statistical Analyses -- 3 Results -- 3.1 Population -- 3.2 Performance of Radiomics -- 4 Discussion -- 5 Conclusion -- References -- Grading and Staging of Bladder Tumors Using Radiomics Analysis in Magnetic Resonance Imaging -- 1 Introduction -- 2 Materials and Methods -- 2.1 Population -- 2.2 MRI Technique -- 2.3 Qualitative Imaging Analysis -- 2.4 Segmentation and Radiomics Features Extraction -- 2.5 Computational and Statistical Analyses -- 3 Results -- 3.1 Population -- 3.2 Performance of Radiomics -- 4 Discussion -- 5 Conclusion -- References -- Combined Data Augmentation for HEp-2 Cells Image Classification -- 1 Introduction -- 2 Materials and Method -- 2.1 Dataset -- 2.2 Basic Image Manipulation -- 2.3 CVAE.
2.4 Experimental Protocol -- 3 Results -- 4 Conclusions -- References -- Multi-modal Medical Imaging Processing (M3IP) -- Harnessing Multi-modality and Expert Knowledge for Adverse Events Prediction in Clinical Notes -- 1 Introduction -- 2 Adverse Events Prediction: Task Formulation -- 3 Data and Information Extraction -- 3.1 Features of Interest -- 3.2 Features Extraction from Structured Data -- 3.3 Features Extraction from Unstructured Data -- 3.4 Multi-modality: Early and Late Fusion -- 4 Training -- 4.1 Datasets and Metrics -- 4.2 Classification Suite -- 4.3 Imbalance Learning -- 5 Results -- 6 Conclusion and Future Work -- References -- A Multimodal Deep Learning Based Approach for Alzheimer's Disease Diagnosis -- 1 Introduction -- 2 Materials and Methods -- 2.1 The Population -- 2.2 Data Preprocessing -- 2.3 The Neural Network -- 2.4 The Proposed Multimodal Approach -- 3 Experimental Set-Up -- 4 Results -- 5 Conclusion -- References -- A Systematic Review of Multimodal Deep Learning Approaches for COVID-19 Diagnosis -- 1 Introduction -- 2 Existing Literature Reviews -- 3 Materials and Methods -- 3.1 Data Sources -- 3.2 Search Strategy and Related Articles -- 4 Results and Discussion -- 5 Conclusions -- References -- A Multi-dimensional Joint ICA Model with Gaussian Copula -- 1 Introduction -- 2 Dataset -- 3 Methods -- 3.1 Conventional Joint ICA -- 3.2 Joint ICA with Different Variances -- 3.3 Proposed Copula Joint ICA -- 4 Implementation -- 4.1 Simulation -- 5 Results -- 6 Conclusion -- References -- Federated Learning in Medical Imaging and Vision (FEDMED) -- Federated Learning for Data and Model Heterogeneity in Medical Imaging -- 1 Introduction -- 2 Related Work -- 2.1 Federated Learning -- 2.2 Model and Data Heterogeneity -- 3 Federated Learning with Heterogeneous Data and Models -- 3.1 Model Heterogeneity.
3.2 Data and Labels Heterogeneity -- 4 Experimental Results -- 4.1 Datasets and Models -- 4.2 Comparison with State-of-the-Art Methods -- 5 Conclusion -- References -- Experience Sharing and Human-in-the-Loop Optimization for Federated Robot Navigation Recommendation -- 1 Introduction -- 2 Learning from Experience -- 3 Recommendation as the Silver Bullet -- 4 Human-in-the-Loop Optimization -- 5 Security-Related Considerations -- 6 Conclusion -- References -- FeDETR: A Federated Approach for Stenosis Detection in Coronary Angiography -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Problem Formulation -- 4 Experimental Evaluation -- 4.1 Dataset -- 4.2 Training Procedure -- 4.3 Results -- 5 Conclusion -- References -- FeDZIO: Decentralized Federated Knowledge Distillation on Edge Devices -- 1 Introduction -- 2 Related Work -- 3 Method -- 4 Performance Evaluation -- 4.1 Dataset -- 4.2 Training Procedure -- 4.3 Experimental Results -- 5 Conclusions -- References -- A Federated Learning Framework for Stenosis Detection -- 1 Introduction -- 2 Material and Methods -- 2.1 Datasets -- 2.2 Experimental Protocol -- 3 Results and Discussion -- 4 Conclusion -- References -- Benchmarking Federated Learning Frameworks for Medical Imaging Tasks -- 1 Introduction -- 2 Related Works -- 3 Experiments -- 4 Results -- 5 Conclusions -- 6 Future Works -- References -- Artificial Intelligence for Digital Humanities (AI4DH) -- Examining the Robustness of an Ensemble Learning Model for Credibility Based Fake News Detection -- 1 Introduction -- 2 Related Works -- 2.1 The Liar Dataset -- 2.2 The FakeNewsNet Dataset -- 2.3 The Fake and Real News Dataset -- 2.4 Spawned Dataset -- 3 Methods -- 3.1 Two-Class Boosted Decision Tree (BDT) -- 3.2 Two Class Neural Network -- 3.3 Mixture of Experts -- 3.4 Two Class Logistic Regression -- 4 Experimental Results.
4.1 Experiments Where the Train and Test Set are the Same -- 4.2 Experiments Where the Train and Test Set are Different -- 5 Conclusion -- References -- Prompt Me a Dataset: An Investigation of Text-Image Prompting for Historical Image Dataset Creation Using Foundation Models -- 1 Introduction -- 2 Current State of the Research -- 3 Pipeline -- 4 Text-Image Prompt Evaluation -- 4.1 A Note on the Environment -- 5 Conclusion -- References -- Artificial Intelligence in Art Generation: An Open Issue -- 1 Introduction -- 2 State of the Art -- 3 The Experts' Point of View -- 3.1 The Philosopher's Point of View -- 3.2 The Art Historian's Point of View -- 3.3 The Computer Scientist's Point of View -- 4 Experimental Results -- 4.1 The Art Exhibition -- 4.2 Users' Feedbacks -- 5 Conclusions -- References -- A Deep Learning Approach for Painting Retrieval Based on Genre Similarity -- 1 Introduction -- 2 Methodology and Experiments -- 2.1 Convolutional Neural Network -- 2.2 Dataset -- 2.3 Nearest Neighbour Algorithm and Similarity Measure -- 2.4 Experiments -- 3 Results -- 3.1 Classifier Performance -- 3.2 Comparison of CBIR Performance Before and After Fine-Tuning with Specific Domain Knowledge -- 3.3 Parameters Optimization of the Approximate Nearest Neighbour Algorithm -- 3.4 Introducing SimArt: A Web Application for Efficiently Searching Similar Artworks -- 4 Discussion and Conclusions -- References -- GeomEthics: Ethical Considerations About Using Artificial Intelligence in Geomatics -- 1 Introduction -- 2 The Use of Artificial Intelligence in Geomatics -- 3 Ethics of Artificial Intelligence in Geomatics -- 3.1 Geospatial Data Fairness -- 3.2 Local Identity -- 3.3 Geo-Privacy -- 4 Conclusions and Future Works -- References -- Fine Art Pattern Extraction and Recognition (FAPER).
Enhancing Preservation and Restoration of Open Reel Audio Tapes Through Computer Vision.
Record Nr. UNISA-996587864003316
Foresti Gian Luca  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Image Analysis and Processing - ICIAP 2023 Workshops [[electronic resource] ] : Udine, Italy, September 11–15, 2023, Proceedings, Part I / / edited by Gian Luca Foresti, Andrea Fusiello, Edwin Hancock
Image Analysis and Processing - ICIAP 2023 Workshops [[electronic resource] ] : Udine, Italy, September 11–15, 2023, Proceedings, Part I / / edited by Gian Luca Foresti, Andrea Fusiello, Edwin Hancock
Autore Foresti Gian Luca
Edizione [1st ed. 2024.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Descrizione fisica 1 online resource (519 pages)
Disciplina 006.37
Altri autori (Persone) FusielloAndrea
HancockEdwin
Collana Lecture Notes in Computer Science
Soggetto topico Computer vision
Computer engineering
Computer networks
Machine learning
Education - Data processing
Pattern recognition systems
Computer Vision
Computer Engineering and Networks
Machine Learning
Computers and Education
Automated Pattern Recognition
ISBN 3-031-51023-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents - Part I -- Contents - Part II -- Industrial Poster Session -- Instance Segmentation Applied to Underground Infrastructures -- 1 Introduction -- 2 Pipes Recognition -- 2.1 Dataset Creation -- 2.2 Dataset Description -- 2.3 Deep Learning Architecture -- 2.4 Classification Overhead -- 3 Experiments -- 3.1 Training -- 3.2 Instance Segmentation Results -- 3.3 Classification Refinement Results -- 4 Conclusion -- References -- Generating Invariance-Based Adversarial Examples: Bringing Humans Back into the Loop -- 1 Introduction -- 2 Adversarial Examples -- 2.1 Sensitivity-Based Adversarial Examples -- 2.2 Invariance-Based Adversarial Examples -- 3 Human Perception -- 4 Experiments -- 4.1 Stimuli -- 4.2 Human Subjects -- 4.3 Eye Tracking Experimental Set-Up -- 4.4 Creation of Occlusion-Based Adversarial Examples -- 5 Results -- 6 Adaptive Approaches -- 7 Conclusion -- References -- MARS: Mask Attention Refinement with Sequential Quadtree Nodes for Car Damage Instance Segmentation -- 1 Introduction -- 2 Related Works -- 3 Proposed Method -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Comparison with SOTA -- 4.3 Implementation Details -- 5 Conclusions -- References -- On-Device Learning with Binary Neural Networks -- 1 Introduction -- 2 Related Literature -- 2.1 Continual Learning -- 2.2 Binary Neural Networks -- 3 On-Device CWR Optimization -- 3.1 Gradients Computation -- 3.2 Quantization Strategy -- 4 Experiments -- 5 Conclusion -- References -- Towards One-Shot PCB Component Detection with YOLO -- 1 Introduction -- 2 Background -- 3 Methodology -- 3.1 Dataset Generation -- 3.2 Improving YOLOv5 Architecture for Small Object Detection -- 3.3 Training Procedure and Evaluation Metrics -- 4 Experimental Results -- 4.1 Experiments with Original YOLOv5 -- 4.2 Experiments with Improved YOLOv5 -- 5 Conclusion.
References -- Wildfires Classification: A Comparative Study -- 1 Introduction -- 2 Datasets for Fire and Smoke Analysis -- 3 Fire Analysis Techniques -- 4 Wildfires Classification -- 4.1 Selected Deep Models -- 4.2 Wildfires Dataset -- 4.3 Deploying the Model on Embedded Systems -- 5 Experimental Results -- 5.1 Results on the FireNet Dataset -- 5.2 Results on Our Wildfires Dataset -- 6 Conclusions and Future Works -- References -- A General Purpose Method for Image Collection Summarization and Exploration -- 1 Introduction and Background -- 2 Proposed Method -- 2.1 Group Selection -- 2.2 Clustering of Pictures Within a Group -- 2.3 Best Picture Selection -- 3 Datasets -- 3.1 Automatic Triage for a Photo Series -- 3.2 Camera Scene Detection Dataset -- 4 Experimental Setup -- 4.1 Data Setup -- 4.2 Evaluation Metrics -- 4.3 Experimental Details -- 5 Results -- 5.1 Subjective Results -- 6 Conclusions -- References -- Automated Identification of Failure Cases in Organ at Risk Segmentation Using Distance Metrics: A Study on CT Data -- 1 Introduction -- 2 Methods and Materials -- 2.1 Dice and Hausdorff Distance Metrics -- 2.2 Dataset -- 2.3 Model Architecture -- 2.4 Experimental Setup -- 3 Results and Discussion -- 4 Conclusion -- References -- Digitizer: A Synthetic Dataset for Well-Log Analysis -- 1 Introduction -- 2 Generating Synthetic Well-Log Curves -- 3 Dataset Analysis -- 4 Conclusions -- References -- CNN-BLSTM Model for Arabic Text Recognition in Unconstrained Captured Identity Documents -- 1 Introduction -- 2 Related Works -- 3 Problem Statement -- 3.1 Identity Document Reading -- 3.2 Arabic Text Recognition -- 4 Proposed Method -- 4.1 Architecture Description -- 4.2 Training Parameters -- 4.3 Data Pre-processing -- 5 Experiments -- 5.1 Dataset -- 5.2 Evaluation Metrics -- 5.3 Model Training -- 5.4 Model Evaluation -- 6 Conclusion -- References.
Advances in Gaze Analysis, Visual attention and Eye-gaze modelling (AGAVE) -- Detection and Localization of Changes in Immersive Virtual Reality -- 1 Introduction -- 2 Experiment and Computational Model -- 2.1 Task -- 2.2 Measures -- 2.3 Apparatus and Procedure -- 2.4 Participants -- 2.5 Computational Model -- 3 Results -- 3.1 Change Localization Experiment -- 3.2 The Proposed Model Accounts for the Patterns of Human Data -- 4 Discussion and Conclusion -- References -- Pain and Fear in the Eyes: Gaze Dynamics Predicts Social Anxiety from Fear Generalisation -- 1 Introduction -- 2 Background and Hypotheses -- 3 Method -- 3.1 Participants and Procedure -- 3.2 Proposed Model and Data Analyses -- 4 Results -- 5 Conclusions -- References -- Eye Gaze Analysis Towards an AI System for Dynamic Content Layout -- 1 Introduction -- 2 AI System -- 3 Experiment -- 3.1 Overview -- 3.2 Set-Up -- 3.3 Clips -- 3.4 Data Analysis -- 4 Results -- 4.1 Graphic Durations -- 4.2 Fixation Durations -- 4.3 Fixation Scores -- 4.4 Region of Interest Hypothesis -- 5 Discussion -- 5.1 Target 1 -- 5.2 Target 2 -- 5.3 Targets 3 and 4 -- 5.4 Target 5 -- 5.5 Target 6 -- 6 Conclusions -- References -- Beyond Vision: Physics Meets AI (BVPAI) -- A Variational AutoEncoder for Model Independent Searches of New Physics at LHC -- 1 Introduction -- 2 The Physics Use-Case: An Effective Field Theory Interpretation of Vector Boson Scattering -- 2.1 Same Sign WW Scattering -- 2.2 Modeling the Anomalies: The SM as an Effective Field Theory -- 3 Variational AutoEncoders -- 3.1 The VAE Architecture -- 3.2 Anomaly Detection with VAEs -- 4 Embedding a Classification Step in the Training to Optimize for Discrimination -- 4.1 Results -- 5 Conclusions and Future Perspectives -- References -- Adaptive Voronoi Binning in Muon Radiography for Detecting Subsurface Cavities.
1 Introduction to Muon Radiography -- 1.1 Cosmic Rays -- 1.2 Muon Radiography -- 2 The MIMA Detector and Its Application at the Temperino Mine -- 3 Adaptive Tessellation Through Voronoi Binning -- 4 Conclusion -- References -- Optimizing Deep Learning Models for Cell Recognition in Fluorescence Microscopy: The Impact of Loss Functions on Performance and Generalization -- 1 Introduction -- 2 Related Works -- 3 Methods -- 3.1 Model Training -- 4 Results -- 5 Discussion -- References -- A New IBA Imaging System for the Transportable MACHINA Accelerator -- 1 Introduction -- 2 Methods -- 3 Tests and Results -- 4 Conclusions -- References -- Abstracts Embeddings Evaluation: A Case Study of Artificial Intelligence and Medical Imaging for the COVID-19 Infection -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Dataset -- 3.2 Label Assignment -- 3.3 Models -- 3.4 Performance Metrics -- 4 Results and Discussions -- 5 Conclusions -- References -- Pigments and Brush Strokes: Investigating the Painting Techniques Using MA-XRF and Laser Profilometry -- 1 Introduction -- 2 Materials and Methods -- 3 Results and Discussion -- 4 Conclusions -- References -- Automatic Affect Analysis and Synthesis (3AS) -- Pain Classification and Intensity Estimation Through the Analysis of Facial Action Units -- 1 Introduction -- 2 Background and Rationales -- 3 Materials and Methods -- 3.1 Datasets -- 3.2 Methods -- 3.3 Results -- 4 Conclusion -- References -- Towards a Better Understanding of Human Emotions: Challenges of Dataset Labeling -- 1 Introduction -- 2 Related Work -- 3 Proposed Emotion Taxonomy -- 4 Experiments -- 4.1 Relabeling the AffectNet Dataset -- 4.2 Results -- 5 Conclusions -- References -- Video-Based Emotion Estimation Using Deep Neural Networks: A Comparative Study -- 1 Introduction -- 2 Related Work -- 3 The OMG-Emotion Dataset.
4 The Video Emotion Estimation Pipeline -- 4.1 Pre-processing -- 4.2 Backbone -- 4.3 Temporal Aggregation -- 4.4 Multi-layer Perceptron -- 4.5 Loss Functions -- 5 Experiments and Results -- 5.1 Ablation Analysis -- 5.2 Model Comparison -- 5.3 State-of-the-Art Comparison -- 6 Conclusions -- A Appendix -- References -- International Contest on Fire Detection (ONFIRE) -- ONFIRE Contest 2023: Real-Time Fire Detection on the Edge -- 1 Introduction -- 2 Related Works -- 3 Contest Dataset and Task -- 4 Evaluation Metrics -- 5 Conclusion -- References -- FIRESTART: Fire Ignition Recognition with Enhanced Smoothing Techniques and Real-Time Tracking -- 1 Introduction -- 2 Materials and Methods -- 2.1 Dataset -- 2.2 Convolutional Neural Networks -- 2.3 Vision Transformers -- 2.4 The Proposed Approach -- 2.5 Metrics -- 3 Experimental Results and Discussion -- 3.1 Experimental Setup -- 3.2 Experimental Results -- 4 Conclusions -- References -- Rapid Fire Detection with Early Exiting -- 1 Introduction -- 2 Related Works -- 2.1 Fire Detection -- 2.2 Advantages of Deep Learning -- 2.3 Early Exiting -- 3 Methodology -- 3.1 Dataset -- 3.2 Model Architectures -- 4 Preliminary Results -- 5 Conclusions -- References -- Recent Advances in Digital Security: Biometrics and Forensics (BIOFORM) -- Morphing-Attacks Against Binary Fingervein Templates -- 1 Introduction -- 2 Morphing of Binary Finger Vein Templates -- 3 Experimental Settings -- 3.1 Assessment Criteria -- 3.2 Data and Recognition Software -- 4 Experimental Results -- 4.1 Threat Evaluation -- 4.2 Detecting Morphed Templates -- 5 Conclusion and Future Work -- References -- A Robust Approach for Crop Misalignment Estimation in Single and Double JPEG Compressed Images -- 1 Introduction -- 2 Proposed Approach -- 3 Experimental Results -- 4 Conclusions -- References.
Human-in-the-Loop Person Re-Identification as a Defence Against Adversarial Attacks.
Record Nr. UNISA-996587863803316
Foresti Gian Luca  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Image Analysis and Processing – ICIAP 2023 [[electronic resource] ] : 22nd International Conference, ICIAP 2023, Udine, Italy, September 11–15, 2023, Proceedings, Part I / / edited by Gian Luca Foresti, Andrea Fusiello, Edwin Hancock
Image Analysis and Processing – ICIAP 2023 [[electronic resource] ] : 22nd International Conference, ICIAP 2023, Udine, Italy, September 11–15, 2023, Proceedings, Part I / / edited by Gian Luca Foresti, Andrea Fusiello, Edwin Hancock
Autore Foresti Gian Luca
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (588 pages)
Disciplina 621.39
004.6
Altri autori (Persone) FusielloAndrea
HancockEdwin
Collana Lecture Notes in Computer Science
Soggetto topico Computer engineering
Computer networks
Machine learning
Education - Data processing
Pattern recognition systems
Computer Engineering and Networks
Machine Learning
Computers and Education
Automated Pattern Recognition
ISBN 3-031-43148-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Image Retrieval in Semiconductor Manufacturing -- Image Retrieval in Semiconductor Manufacturing -- Self-Similarity Block for Deep Image Denoising -- A request for clarity over the End of Sequence token in the Self-Critical Sequence Training -- Shallow camera pipeline for night photography enhancement -- GCK-Maps: a scene unbiased representation for efficient Human Action Recognition -- Autism spectrum disorder identification from visual exploration of images -- Target-Driven One-Shot Unsupervised Domain Adaptation -- Combining identity features and artifact analysis for Differential Morphing Attack Detection -- SynthCap: Augmenting Transformers with Synthetic Data for Image Captioning -- An Effective CNN-Based Super Resolution Method for Video Coding -- Medical Transformers for Boosting Automatic Grading of Colon Carcinoma in Histological Images -- UAV Multi-Object Tracking by combining two Deep Neural Architectures -- Consensus Ranking for Efficient Face Image Retrieval: A Novel Method for Maximising Precision and Recall -- Towards Explainable Navigation and Recounting -- Towards facial expression robustness in multi-scale wild environments -- Depth camera face recognition by normalized fractal encodings -- Automatic Generation of Semantic Parts for Face Image Synthesis -- Improved Bilinear Pooling For Real-Time Pose Event Camera Relocalisation -- End-to-End Asbestos Roof Detection on Orthophotos Using Transformer-based YOLO Deep Neural Network -- OpenFashionCLIP: Vision-and-Language Contrastive Learning with Open-Source Fashion Data -- UAV Multi-Object Tracking by combining two Deep Neural Architectures -- GLR: Gradient-based Learning Rate scheduler -- A Large-scale Analysis of Athletes’ Cumulative Race Time in Running Events -- Uncovering Lies: Deception Detection in a Rolling-Dice Experiment -- Active Class Selection for Dataset Acquisition in Sign Language Recognition -- MC-GTA: A Synthetic Benchmark for Multi-Camera Vehicle Tracking -- A differentiable entropy model for learned image compression -- Learning Landmarks Motion from Speech for Speaker-Agnostic 3D Talking Heads Generation -- SCENE-pathy: Capturing the Visual Selective Attention of People Towards Scene Elements -- Not with my name! Inferring artists’ names of input strings employed by Diffusion Models -- Benchmarking of Blind Video Deblurring Methods on Long Exposure and Resource Poor Settings -- LieToMe: An LSTM-based Method for Deception Detection by Hand Movements -- Spatial Transformer Generative Adversarial Network for Image Super-Resolution -- Real-Time GAN-based Model for Underwater Image Enhancement -- HERO: A Multi-Modal Approach on Mobile Devices for Visual-Aware Conversational Assistance in Industrial Domains -- A Computer Vision-Based water level monitoring system for touchless and sustainable water dispensing -- Smoothing and Transition Matrices estimation to learn with Noisy Labels -- Semi-supervised classification for Remote Sensing datasets -- Exploiting Exif Data to Improve Image Classification using Convolutional Neural Networks -- Weak Segmentation-Guided GAN for realistic color edition -- Hand Gesture Recognition exploiting Handcrafted Features and LSTM -- An Optimized Pipeline for Image-Based Localization in Museums from Egocentric Images -- Annotating the Inferior Alveolar Canal: the Ultimate Tool -- Active Class Selection for Dataset Acquisition in Sign Language Recognition -- Enhancing PFI Prediction with GDS-MIL: A Graph-based Dual Stream MIL Approach.
Record Nr. UNINA-9910743683803321
Foresti Gian Luca  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Image Analysis and Processing – ICIAP 2023 [[electronic resource] ] : 22nd International Conference, ICIAP 2023, Udine, Italy, September 11–15, 2023, Proceedings, Part I / / edited by Gian Luca Foresti, Andrea Fusiello, Edwin Hancock
Image Analysis and Processing – ICIAP 2023 [[electronic resource] ] : 22nd International Conference, ICIAP 2023, Udine, Italy, September 11–15, 2023, Proceedings, Part I / / edited by Gian Luca Foresti, Andrea Fusiello, Edwin Hancock
Autore Foresti Gian Luca
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (588 pages)
Disciplina 621.39
004.6
Altri autori (Persone) FusielloAndrea
HancockEdwin
Collana Lecture Notes in Computer Science
Soggetto topico Computer engineering
Computer networks
Machine learning
Education - Data processing
Pattern recognition systems
Computer Engineering and Networks
Machine Learning
Computers and Education
Automated Pattern Recognition
ISBN 3-031-43148-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Image Retrieval in Semiconductor Manufacturing -- Image Retrieval in Semiconductor Manufacturing -- Self-Similarity Block for Deep Image Denoising -- A request for clarity over the End of Sequence token in the Self-Critical Sequence Training -- Shallow camera pipeline for night photography enhancement -- GCK-Maps: a scene unbiased representation for efficient Human Action Recognition -- Autism spectrum disorder identification from visual exploration of images -- Target-Driven One-Shot Unsupervised Domain Adaptation -- Combining identity features and artifact analysis for Differential Morphing Attack Detection -- SynthCap: Augmenting Transformers with Synthetic Data for Image Captioning -- An Effective CNN-Based Super Resolution Method for Video Coding -- Medical Transformers for Boosting Automatic Grading of Colon Carcinoma in Histological Images -- UAV Multi-Object Tracking by combining two Deep Neural Architectures -- Consensus Ranking for Efficient Face Image Retrieval: A Novel Method for Maximising Precision and Recall -- Towards Explainable Navigation and Recounting -- Towards facial expression robustness in multi-scale wild environments -- Depth camera face recognition by normalized fractal encodings -- Automatic Generation of Semantic Parts for Face Image Synthesis -- Improved Bilinear Pooling For Real-Time Pose Event Camera Relocalisation -- End-to-End Asbestos Roof Detection on Orthophotos Using Transformer-based YOLO Deep Neural Network -- OpenFashionCLIP: Vision-and-Language Contrastive Learning with Open-Source Fashion Data -- UAV Multi-Object Tracking by combining two Deep Neural Architectures -- GLR: Gradient-based Learning Rate scheduler -- A Large-scale Analysis of Athletes’ Cumulative Race Time in Running Events -- Uncovering Lies: Deception Detection in a Rolling-Dice Experiment -- Active Class Selection for Dataset Acquisition in Sign Language Recognition -- MC-GTA: A Synthetic Benchmark for Multi-Camera Vehicle Tracking -- A differentiable entropy model for learned image compression -- Learning Landmarks Motion from Speech for Speaker-Agnostic 3D Talking Heads Generation -- SCENE-pathy: Capturing the Visual Selective Attention of People Towards Scene Elements -- Not with my name! Inferring artists’ names of input strings employed by Diffusion Models -- Benchmarking of Blind Video Deblurring Methods on Long Exposure and Resource Poor Settings -- LieToMe: An LSTM-based Method for Deception Detection by Hand Movements -- Spatial Transformer Generative Adversarial Network for Image Super-Resolution -- Real-Time GAN-based Model for Underwater Image Enhancement -- HERO: A Multi-Modal Approach on Mobile Devices for Visual-Aware Conversational Assistance in Industrial Domains -- A Computer Vision-Based water level monitoring system for touchless and sustainable water dispensing -- Smoothing and Transition Matrices estimation to learn with Noisy Labels -- Semi-supervised classification for Remote Sensing datasets -- Exploiting Exif Data to Improve Image Classification using Convolutional Neural Networks -- Weak Segmentation-Guided GAN for realistic color edition -- Hand Gesture Recognition exploiting Handcrafted Features and LSTM -- An Optimized Pipeline for Image-Based Localization in Museums from Egocentric Images -- Annotating the Inferior Alveolar Canal: the Ultimate Tool -- Active Class Selection for Dataset Acquisition in Sign Language Recognition -- Enhancing PFI Prediction with GDS-MIL: A Graph-based Dual Stream MIL Approach.
Record Nr. UNISA-996550561403316
Foresti Gian Luca  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Image Analysis and Processing – ICIAP 2023 [[electronic resource] ] : 22nd International Conference, ICIAP 2023, Udine, Italy, September 11–15, 2023, Proceedings, Part II / / edited by Gian Luca Foresti, Andrea Fusiello, Edwin Hancock
Image Analysis and Processing – ICIAP 2023 [[electronic resource] ] : 22nd International Conference, ICIAP 2023, Udine, Italy, September 11–15, 2023, Proceedings, Part II / / edited by Gian Luca Foresti, Andrea Fusiello, Edwin Hancock
Autore Foresti Gian Luca
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (589 pages)
Disciplina 006.37
Altri autori (Persone) FusielloAndrea
HancockEdwin
Collana Lecture Notes in Computer Science
Soggetto topico Computer vision
Pattern recognition systems
Computer engineering
Computer networks
Machine learning
Education - Data processing
Computer Vision
Automated Pattern Recognition
Computer Engineering and Networks
Machine Learning
Computers and Education
ISBN 3-031-43153-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Buffer-MIL: Robust Multi-instance Learning with a Buffer-based Approach -- Quasi-Online Detection of Take and Release Actions from Egocentric Videos -- Hashing for Structure-based Anomaly Detection -- Augmentation based on artificial occlusions for resilient instance segmentation -- Unsupervised Video Anomaly Detection with Diffusion Models Conditioned on Compact Motion Representations -- VM-NeRF: Tackling Sparsity in NeRF with View Morphing -- MOVING: a MOdular and flexible platform for embodied VIsual NaviGation -- Evaluation of 3D reconstruction pipelines under varying imaging conditions -- CarPatch: A Synthetic Benchmark for Radiance Field Evaluation on Vehicle Components -- Obstacle Avoidance and Interaction in Extended Reality: An Approach based on 3D Object Detection -- HMPD: a novel dataset for microplastics classification with digital holography -- Early detection of hip periprosthetic joint infections through CNN on Computed Tomography images -- Many-to-Many metrics: a new approach to evaluate the performance of structural damage detection networks -- Deepfakes Audio Detection leveraging audio spectrogram and Convolutional Neural Networks -- A deep Natural Language Inference predictor without language-specific training data -- Time-aware Circulant Matrices for Question-based Temporal Localization -- Enhancing Open-Vocabulary Semantic Segmentation with Prototype Retrieval -- Lightweight Blur Kernel Estimation Network for Blind Image Super-Resolution -- Hierarchical Pretrained Backbone Vision Transformer for Image Classification in Histopathology -- On using rPPG signals for DeepFake detection: a cautionary note -- An unsupervised learning approach to resolve phenotype to genotype mapping in budding yeasts vacuoles -- Food image classification: the benefit of in-domain transfer learning -- LCMV: Lightweight Classification Module for Video Domain Adaptation -- FEAD-D: Facial Expression Analysis in Deepfake Detection -- Large Class Separation is not what you need for Relational Reasoning-based OOD Detection -- BLUES: Before-reLU-EStimates Bayesian Inference for Crowd Counting -- Two is Better than One: Achieving High-Quality 3D Scene Modeling with a NeRF Ensemble -- BHAC-MRI: Backdoor & Hybrid Attacks on MRI Brain Tumor Classification Using CNN -- Unveiling the Impact of Image Transformations on Deepfake Detection: An Experimental Analysis -- Extrinsic Calibration of Multiple Depth Cameras for 3D Face Reconstruction -- A Deep Learning based Approach for Synthesizing Realistic Depth Maps -- Specialise to Generalise: the Person Re-identification Case -- Enhancing Hierarchical Vector Quantized Autoencoders for Image Synthesis through Multiple Decoders -- Dynamic Local Filters in Graph Convolutional Neural Networks -- An AI-Driven Prototype for Groundwater Level Prediction: Exploring the Gorgovivo Spring Case Study -- DiffDefense: Defending against Adversarial Attacks via Diffusion Models -- Exploring Audio Compression as Image Completion in Time-Frequency Domain -- Fuzzy Logic Visual Network (FLVN): A neuro-symbolic approach for visual features matching -- CISPc: Embedding images and point clouds in a joint concept space by contrastive learning -- Budget-Aware Pruning for Multi-Domain Learning -- Sparse Double Descent in Vision Transformers: real or phantom threat? -- Video Sonification to Support Visually Impaired People: the VISaVIS approach -- Minimizing Energy Consumption of Deep Learning Models by Energy-Aware Training -- The Specchieri MarVen Dataset: an Abbreviation-rich Dataset in Venetian Idiom -- Compensation for Patient Movements in CBCT Imaging for Dental Applications -- Spatial Exploration Indicators in the Remote Assessment of Visual Neglect.
Record Nr. UNISA-996550560903316
Foresti Gian Luca  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Image Analysis and Processing – ICIAP 2023 : 22nd International Conference, ICIAP 2023, Udine, Italy, September 11–15, 2023, Proceedings, Part II / / edited by Gian Luca Foresti, Andrea Fusiello, Edwin Hancock
Image Analysis and Processing – ICIAP 2023 : 22nd International Conference, ICIAP 2023, Udine, Italy, September 11–15, 2023, Proceedings, Part II / / edited by Gian Luca Foresti, Andrea Fusiello, Edwin Hancock
Autore Foresti Gian Luca
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (589 pages)
Disciplina 006.37
Altri autori (Persone) FusielloAndrea
HancockEdwin
Collana Lecture Notes in Computer Science
Soggetto topico Computer vision
Pattern recognition systems
Computer engineering
Computer networks
Machine learning
Education - Data processing
Computer Vision
Automated Pattern Recognition
Computer Engineering and Networks
Machine Learning
Computers and Education
ISBN 3-031-43153-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Buffer-MIL: Robust Multi-instance Learning with a Buffer-based Approach -- Quasi-Online Detection of Take and Release Actions from Egocentric Videos -- Hashing for Structure-based Anomaly Detection -- Augmentation based on artificial occlusions for resilient instance segmentation -- Unsupervised Video Anomaly Detection with Diffusion Models Conditioned on Compact Motion Representations -- VM-NeRF: Tackling Sparsity in NeRF with View Morphing -- MOVING: a MOdular and flexible platform for embodied VIsual NaviGation -- Evaluation of 3D reconstruction pipelines under varying imaging conditions -- CarPatch: A Synthetic Benchmark for Radiance Field Evaluation on Vehicle Components -- Obstacle Avoidance and Interaction in Extended Reality: An Approach based on 3D Object Detection -- HMPD: a novel dataset for microplastics classification with digital holography -- Early detection of hip periprosthetic joint infections through CNN on Computed Tomography images -- Many-to-Many metrics: a new approach to evaluate the performance of structural damage detection networks -- Deepfakes Audio Detection leveraging audio spectrogram and Convolutional Neural Networks -- A deep Natural Language Inference predictor without language-specific training data -- Time-aware Circulant Matrices for Question-based Temporal Localization -- Enhancing Open-Vocabulary Semantic Segmentation with Prototype Retrieval -- Lightweight Blur Kernel Estimation Network for Blind Image Super-Resolution -- Hierarchical Pretrained Backbone Vision Transformer for Image Classification in Histopathology -- On using rPPG signals for DeepFake detection: a cautionary note -- An unsupervised learning approach to resolve phenotype to genotype mapping in budding yeasts vacuoles -- Food image classification: the benefit of in-domain transfer learning -- LCMV: Lightweight Classification Module for Video Domain Adaptation -- FEAD-D: Facial Expression Analysis in Deepfake Detection -- Large Class Separation is not what you need for Relational Reasoning-based OOD Detection -- BLUES: Before-reLU-EStimates Bayesian Inference for Crowd Counting -- Two is Better than One: Achieving High-Quality 3D Scene Modeling with a NeRF Ensemble -- BHAC-MRI: Backdoor & Hybrid Attacks on MRI Brain Tumor Classification Using CNN -- Unveiling the Impact of Image Transformations on Deepfake Detection: An Experimental Analysis -- Extrinsic Calibration of Multiple Depth Cameras for 3D Face Reconstruction -- A Deep Learning based Approach for Synthesizing Realistic Depth Maps -- Specialise to Generalise: the Person Re-identification Case -- Enhancing Hierarchical Vector Quantized Autoencoders for Image Synthesis through Multiple Decoders -- Dynamic Local Filters in Graph Convolutional Neural Networks -- An AI-Driven Prototype for Groundwater Level Prediction: Exploring the Gorgovivo Spring Case Study -- DiffDefense: Defending against Adversarial Attacks via Diffusion Models -- Exploring Audio Compression as Image Completion in Time-Frequency Domain -- Fuzzy Logic Visual Network (FLVN): A neuro-symbolic approach for visual features matching -- CISPc: Embedding images and point clouds in a joint concept space by contrastive learning -- Budget-Aware Pruning for Multi-Domain Learning -- Sparse Double Descent in Vision Transformers: real or phantom threat? -- Video Sonification to Support Visually Impaired People: the VISaVIS approach -- Minimizing Energy Consumption of Deep Learning Models by Energy-Aware Training -- The Specchieri MarVen Dataset: an Abbreviation-rich Dataset in Venetian Idiom -- Compensation for Patient Movements in CBCT Imaging for Dental Applications -- Spatial Exploration Indicators in the Remote Assessment of Visual Neglect.
Record Nr. UNINA-9910743688803321
Foresti Gian Luca  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui