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Pattern Recognition and Image Analysis [[electronic resource] ] : 11th Iberian Conference, IbPRIA 2023, Alicante, Spain, June 27–30, 2023, Proceedings / / edited by Antonio Pertusa, Antonio Javier Gallego, Joan Andreu Sánchez, Inês Domingues
Pattern Recognition and Image Analysis [[electronic resource] ] : 11th Iberian Conference, IbPRIA 2023, Alicante, Spain, June 27–30, 2023, Proceedings / / edited by Antonio Pertusa, Antonio Javier Gallego, Joan Andreu Sánchez, Inês Domingues
Autore Pertusa Antonio
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (735 pages)
Disciplina 006.4
Altri autori (Persone) GallegoAntonio Javier
SánchezJoan Andreu
DominguesInês
Collana Lecture Notes in Computer Science
Soggetto topico Pattern recognition systems
Education—Data processing
Social sciences—Data processing
Computer vision
Machine learning
Automated Pattern Recognition
Computers and Education
Computer Application in Social and Behavioral Sciences
Computer Vision
Machine Learning
ISBN 3-031-36616-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Machine Learning -- CCLM: Class-conditional Label Noise Modelling -- Addressing class imbalance in Multilabel Prototype Generation for k-Nearest Neighbor classification -- Time series imputation in faulty systems -- DARTS with degeneracy correction -- A fuzzy logic inference system for display characterization -- Learning Semantic-Visual Embeddings with a Priority Queue -- Learning Semantic-Visual Embeddings with a Priority Queue -- Continual vocabularies to tackle the catastrophic forgetting problem in Machine Translation -- Evaluating Domain Generalization in Kitchen Utensils Classification -- Document Analysis -- Segmentation of Large Historical Manuscript Bundles into Multi-page Deeds -- A Study of Augmentation Methods for Handwritten Stenography Recognition -- Lifelong Learning for Document Image Binarization: A Experimental Study -- Test-Time Augmentation for Document Image Binarization -- A Weakly-Supervised Approach for Layout Analysis in Music Score Images -- ResPho(SC)Net: A Zero-Shot Learning Framework for Norwegian Handwritten Word Image Recognition -- Computer Vision -- DeepArUco: Marker detection and classification in challenging lightning conditions -- Automated Detection and Identification of Olive Fruit Fly using YOLOv7 Algorithm -- Learning to search for and detect objects in foveal images using deep learning -- Relation networks for few-shot video object detection -- Optimal Wavelength Selection for Deep Learning from Hyperspectral Images -- Can representation learning for multimodal image registration be improved by supervision of intermediate layers? -- Interpretability-Guided Human Feedback During Neural Network Training -- Calibration of Non-Central Conical Catadioptric Systems from Parallel Lines -- S² -LOR: Supervised Stream Learning for Object Recognition -- Evaluation of Regularization Techniques for Transformers-Based Models -- 3D Computer Vision -- Guided depth completion using active infrared images in Time of Flight system -- StOCaMo: Online Calibration Monitoring for Stereo Cameras -- Smart-Tree: Neural Medial Axis Approximation of Point Clouds for 3D Tree Skeletonization -- A Measure of Tortuosity for 3D Curves: Identifying 3D beating patterns of sperm flagella -- The ETS2 Dataset, synthetic data from video games for monocular depth estimation -- Computer Vision Applications -- Multimodal Human Pose feature fusion for Gait recognition -- Proxemics-Net: automatic proxemics recognition in images -- Lightweight Vision Transformers for Face Verification in the Wild -- Py4MER: a CTC-based Mathematical Expression Recognition System -- Hierarchical Line Extremity Segmentation U-Net for the SoccerNet 2022 Calibration Challenge - Pitch Localization -- Object Localization with Multiplanar Fiducial Markers: Accurate Pose Estimation -- Real-time unsupervised object localization on the edge for airport video surveillance -- Identifying Thermokarst Lakes Using Discrete Wavelet Transform–Based Deep Learning Framework -- Object Detection for Rescue Operations by High-altitude Infrared Thermal Imaging Collected by Unmanned Aerial Vehicles -- Medical Imaging & Applications -- Inter vs. Intra Domain Study of COVID Chest X-Ray Classification with Imbalanced Datasets -- Automatic Eye-Tracking-Assisted Chest Radiography Pathology Screening -- Deep Neural Networks to distinguish between Crohn’s disease and Ulcerative colitis -- Few-shot image classification for automatic COVID-19 diagnosis -- An ensemble-based phenotype classifier to diagnose Crohn’s disease from 16s rRNA gene sequences -- Synthetic spermatozoa video sequences generation using Adversarial Imitation Learning -- A Deep Approach for Volumetric Tractography Segmentation -- MicrogliaJ: an Automatic Tool for Microglial Cell Detection and Segmentation -- Automated Orientation Detection of 3D Head Reconstructions from sMRI using Multiview Orthographic Projections: An Image Classification-Based Approach -- Machine Learning Applications -- Enhancing Transferability of Adversarial Audio in Speaker Recognition Systems -- Fishing Gear Classification from Vessel Trajectories and Velocity Profiles: Database and Benchmark -- Multi-view Infant Cry Classification -- Study and automatic translation of Toki Pona -- Detecting Loose Wheel Bolts of a Vehicle using Accelerometers in the Chassis -- Clustering ECG time series for the quantification of physiological reactions to emotional stimuli -- Predicting the Subjective Responses’ Emotion in Dialogues with Multi-Task Learning -- Few-shot learning for prediction of electricity consumption patterns.
Record Nr. UNISA-996538665603316
Pertusa Antonio  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Pattern Recognition and Image Analysis : 11th Iberian Conference, IbPRIA 2023, Alicante, Spain, June 27–30, 2023, Proceedings / / edited by Antonio Pertusa, Antonio Javier Gallego, Joan Andreu Sánchez, Inês Domingues
Pattern Recognition and Image Analysis : 11th Iberian Conference, IbPRIA 2023, Alicante, Spain, June 27–30, 2023, Proceedings / / edited by Antonio Pertusa, Antonio Javier Gallego, Joan Andreu Sánchez, Inês Domingues
Autore Pertusa Antonio
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (735 pages)
Disciplina 006.4
006.42
Altri autori (Persone) GallegoAntonio Javier
SánchezJoan Andreu
DominguesInês
Collana Lecture Notes in Computer Science
Soggetto topico Pattern recognition systems
Education—Data processing
Social sciences—Data processing
Computer vision
Machine learning
Automated Pattern Recognition
Computers and Education
Computer Application in Social and Behavioral Sciences
Computer Vision
Machine Learning
ISBN 3-031-36616-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Machine Learning -- CCLM: Class-conditional Label Noise Modelling -- Addressing class imbalance in Multilabel Prototype Generation for k-Nearest Neighbor classification -- Time series imputation in faulty systems -- DARTS with degeneracy correction -- A fuzzy logic inference system for display characterization -- Learning Semantic-Visual Embeddings with a Priority Queue -- Learning Semantic-Visual Embeddings with a Priority Queue -- Continual vocabularies to tackle the catastrophic forgetting problem in Machine Translation -- Evaluating Domain Generalization in Kitchen Utensils Classification -- Document Analysis -- Segmentation of Large Historical Manuscript Bundles into Multi-page Deeds -- A Study of Augmentation Methods for Handwritten Stenography Recognition -- Lifelong Learning for Document Image Binarization: A Experimental Study -- Test-Time Augmentation for Document Image Binarization -- A Weakly-Supervised Approach for Layout Analysis in Music Score Images -- ResPho(SC)Net: A Zero-Shot Learning Framework for Norwegian Handwritten Word Image Recognition -- Computer Vision -- DeepArUco: Marker detection and classification in challenging lightning conditions -- Automated Detection and Identification of Olive Fruit Fly using YOLOv7 Algorithm -- Learning to search for and detect objects in foveal images using deep learning -- Relation networks for few-shot video object detection -- Optimal Wavelength Selection for Deep Learning from Hyperspectral Images -- Can representation learning for multimodal image registration be improved by supervision of intermediate layers? -- Interpretability-Guided Human Feedback During Neural Network Training -- Calibration of Non-Central Conical Catadioptric Systems from Parallel Lines -- S² -LOR: Supervised Stream Learning for Object Recognition -- Evaluation of Regularization Techniques for Transformers-Based Models -- 3D Computer Vision -- Guided depth completion using active infrared images in Time of Flight system -- StOCaMo: Online Calibration Monitoring for Stereo Cameras -- Smart-Tree: Neural Medial Axis Approximation of Point Clouds for 3D Tree Skeletonization -- A Measure of Tortuosity for 3D Curves: Identifying 3D beating patterns of sperm flagella -- The ETS2 Dataset, synthetic data from video games for monocular depth estimation -- Computer Vision Applications -- Multimodal Human Pose feature fusion for Gait recognition -- Proxemics-Net: automatic proxemics recognition in images -- Lightweight Vision Transformers for Face Verification in the Wild -- Py4MER: a CTC-based Mathematical Expression Recognition System -- Hierarchical Line Extremity Segmentation U-Net for the SoccerNet 2022 Calibration Challenge - Pitch Localization -- Object Localization with Multiplanar Fiducial Markers: Accurate Pose Estimation -- Real-time unsupervised object localization on the edge for airport video surveillance -- Identifying Thermokarst Lakes Using Discrete Wavelet Transform–Based Deep Learning Framework -- Object Detection for Rescue Operations by High-altitude Infrared Thermal Imaging Collected by Unmanned Aerial Vehicles -- Medical Imaging & Applications -- Inter vs. Intra Domain Study of COVID Chest X-Ray Classification with Imbalanced Datasets -- Automatic Eye-Tracking-Assisted Chest Radiography Pathology Screening -- Deep Neural Networks to distinguish between Crohn’s disease and Ulcerative colitis -- Few-shot image classification for automatic COVID-19 diagnosis -- An ensemble-based phenotype classifier to diagnose Crohn’s disease from 16s rRNA gene sequences -- Synthetic spermatozoa video sequences generation using Adversarial Imitation Learning -- A Deep Approach for Volumetric Tractography Segmentation -- MicrogliaJ: an Automatic Tool for Microglial Cell Detection and Segmentation -- Automated Orientation Detection of 3D Head Reconstructions from sMRI using Multiview Orthographic Projections: An Image Classification-Based Approach -- Machine Learning Applications -- Enhancing Transferability of Adversarial Audio in Speaker Recognition Systems -- Fishing Gear Classification from Vessel Trajectories and Velocity Profiles: Database and Benchmark -- Multi-view Infant Cry Classification -- Study and automatic translation of Toki Pona -- Detecting Loose Wheel Bolts of a Vehicle using Accelerometers in the Chassis -- Clustering ECG time series for the quantification of physiological reactions to emotional stimuli -- Predicting the Subjective Responses’ Emotion in Dialogues with Multi-Task Learning -- Few-shot learning for prediction of electricity consumption patterns.
Record Nr. UNINA-9910734892303321
Pertusa Antonio  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications [[electronic resource] ] : 26th Iberoamerican Congress, CIARP 2023, Coimbra, Portugal, November 27–30, 2023, Proceedings, Part I / / edited by Verónica Vasconcelos, Inês Domingues, Simão Paredes
Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications [[electronic resource] ] : 26th Iberoamerican Congress, CIARP 2023, Coimbra, Portugal, November 27–30, 2023, Proceedings, Part I / / edited by Verónica Vasconcelos, Inês Domingues, Simão Paredes
Autore Vasconcelos Verónica
Edizione [1st ed. 2024.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Descrizione fisica 1 online resource (764 pages)
Disciplina 006.4
Altri autori (Persone) DominguesInês
ParedesSimão
Collana Lecture Notes in Computer Science
Soggetto topico Pattern recognition systems
Machine learning
Computer vision
Computer engineering
Computer networks
Application software
Automated Pattern Recognition
Machine Learning
Computer Vision
Computer Engineering and Networks
Computer and Information Systems Applications
ISBN 3-031-49018-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents - Part I -- Contents - Part II -- Deblur Capsule Networks -- 1 Introduction -- 2 Related Works -- 3 Deblur Capsule Networks -- 3.1 Blur Type Classification -- 3.2 Point Spread Function Reconstruction -- 3.3 Image Deep Regularized Deconvolution -- 4 Experiments and Analysis -- 4.1 DbCN Optimization Procedure -- 4.2 Synthetic Camera Motion Blur -- 4.3 Synthetic Multi-domain Blur -- 4.4 Ablation Study -- 5 Conclusions and Future Works -- References -- Graph Embedding of Almost Constant Large Graphs -- 1 Introduction -- 2 Graphs and Graph Embedding -- 3 GraphFingerprint: An Embedding for Almost Constant Graphs -- 3.1 Algorithm Input Parameters -- 3.2 Local Substructures -- 3.3 GraphFingerprint Definition -- 3.4 GraphFingerprint Examples -- 4 Experimental Section -- 4.1 From Metal-Oxide Nanocompound to GraphFingerprint -- 4.2 Toxicity Prediction Based on Global Features -- 4.3 Toxicity Prediction Based on GraphFingerprints -- 4.4 Toxicity Prediction Based on Global Features and GraphFingerprints -- 5 Conclusions -- 6 Future Work -- References -- Feature Importance for Clustering -- 1 Introduction -- 2 Cluster Analysis -- 3 Proposed Methods -- 3.1 Prototype-Based Feature Importance -- 3.2 SHAP-Based Feature Importance -- 4 Experimental Simulations -- 5 Concluding Remarks -- References -- Uncovering Manipulated Files Using Mathematical Natural Laws -- 1 Introduction -- 2 Related Work -- 3 Benford's Law Fundamentals -- 3.1 Benford's Law Statement -- 4 Dataset -- 5 Benford's Law-Based Method -- 5.1 Pre-processing -- 5.2 Processing -- 5.3 Median Absolute Deviation -- 5.4 Evaluation Metrics -- 6 Results -- 6.1 Analysis of Results -- 7 Conclusions and Future Work -- References -- History Based Incremental Singular Value Decomposition for Background Initialization and Foreground Segmentation -- 1 Introduction.
2 Related Work -- 2.1 Identification of SFOs -- 2.2 Background Dependency -- 3 Methodology -- 3.1 Notation and Preliminaries -- 3.2 Computation of Incremental SVD -- 3.3 History Based Incremental SVD (hi-SVD) -- 4 Experimental Results -- 4.1 Datasets -- 4.2 SFO Status Identification Experiment -- 4.3 Foreground Segmentation Experiment -- 5 Conclusion -- References -- Vehicle Re-Identification Based on Unsupervised Domain Adaptation by Incremental Generation of Pseudo-Labels -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 DBSCAN Pseudo-Labels -- 3.2 Fine-Tuning -- 3.3 Unsupervised Domain Adaptation -- 4 Experimental Validation -- 4.1 Dataset and Evaluation Environment -- 4.2 Implementation Details -- 4.3 Ablation Study for Eps-Neighborhood in DBSCAN -- 4.4 Ablation Study for Increasing the Number of Cycles in the Generation of Pseudo-Labels -- 5 Conclusions -- References -- How to Turn Your Camera into a Perfect Pinhole Model -- 1 Introduction -- 2 Methods -- 2.1 Gaussian Processes -- 2.2 Constructing an Ideal Pinhole Camera -- 2.3 The Datasets -- 3 Results -- 3.1 Collineation Assumption -- 3.2 Reprojection Error -- 3.3 Distortion Removal -- 4 Discussion -- 5 Conclusion -- A Zhang's Method -- B Simplified Zhang's Method -- References -- Single Image HDR Synthesis with Histogram Learning -- 1 Introduction -- 2 Method -- 2.1 LDR2EDR by Histogram and Resolution difference -- 2.2 EDR2HDR by Cumulative Histogram Learning -- 2.3 Fine-Tuning with Reinforcement Learning -- 3 Experiments -- 4 Conclusion -- References -- But That's Not Why: Inference Adjustment by Interactive Prototype Revision -- 1 Introduction -- 2 Prototype-Based Learning -- 3 Interactive Prototype Revision -- 4 Results -- 5 Conclusion -- References -- Teaching Practices Analysis Through Audio Signal Processing -- 1 Introduction -- 2 Related Work -- 3 Dataset Description.
4 Classroom Activity Detection -- 4.1 Training and Testing Data -- 4.2 Unsupervised Diarization Approach -- 4.3 Supervised Audio Classification -- 4.4 Experiments and Results -- 5 Additional Tools for English Lessons Analysis -- 5.1 Language Detection -- 5.2 Key Phrases Matching -- 5.3 User Interface for Education Technicians -- 6 Conclusions and Further Work -- References -- Time Distributed Multiview Representation for Speech Emotion Recognition -- 1 Introduction -- 2 Related Work -- 3 Proposed Strategy -- 3.1 Database Description -- 3.2 General Architecture -- 3.3 Step 1 - Initial Procedures -- 3.4 Steps 2 and 3 - Algorithms and Combiner -- 3.5 Steps 4 and 5 - LSTM and Emotion Classification -- 4 Experimental Results -- 4.1 Experiment 1 - Results for All RAVDESS Database -- 4.2 Experiment 2 - Database Divided by Intensity -- 4.3 Experiment 3 - LOSO Protocol -- 5 Discussions -- 6 Conclusion -- References -- Detection of Covid-19 in Chest X-Ray Images Using Percolation Features and Hermite Polynomial Classification -- 1 Introduction -- 2 Materials and Methods -- 2.1 Image Database -- 2.2 Methodology -- 3 Results and Discussion -- 3.1 Feature Evaluation -- 3.2 Performance of the HP Classifier -- 4 Conclusion -- References -- Abandoned Object Detection Using Persistent Homology -- 1 Introduction -- 2 From Background Subtraction to Simplicial Complex -- 3 Surveillance Points -- 4 Filtration -- 5 Persistent Homology and Topological Signature -- 6 Detecting Abandoned Objects -- 7 Experimental Results -- 8 Conclusion and Future Works -- References -- Interactive Segmentation with Incremental Watershed Cuts -- 1 Introduction -- 2 Watershed Cuts -- 3 Semi-supervised Watershed Cut Algorithm with Interactions -- 3.1 Tree-Node Marking -- 3.2 Pixel Labeling -- 3.3 Incremental Workflow -- 4 Experiments -- 4.1 Experiment with User Generated Seeds.
4.2 Experiment with Randomly Generated Seeds -- 5 Conclusion -- References -- Supervised Learning of Hierarchical Image Segmentation -- 1 Introduction -- 2 Ultrametric Dataset -- 3 Model -- 4 Evaluation Metrics -- 5 Experiments -- 6 Conclusion -- References -- Unveiling the Influence of Image Super-Resolution on Aerial Scene Classification -- 1 Introduction -- 2 Super-Resolution -- 2.1 Super-Resolution Convolution Neural Network (SRCNN) -- 2.2 Modified 3D Residual-in-Residual Dense Block (m3DRRDB) -- 2.3 SwinIR Transformer -- 3 Scene Classification -- 4 Experiments -- 4.1 Datasets -- 4.2 Experimental Settings -- 5 Results and Discussion -- 5.1 Experiment 1: Ranking of Super-Resolution Methods -- 5.2 Experiment 2: Impact of Super-Resolution on Aerial Scene Classification -- 6 Conclusion -- References -- Weeds Classification with Deep Learning: An Investigation Using CNN, Vision Transformers, Pyramid Vision Transformers, and Ensemble Strategy -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Datasets -- 3.2 Models -- 3.3 Ensemble -- 3.4 Evaluation -- 3.5 Training Configuration -- 3.6 Execution Environment -- 4 Results and Discussion -- 5 Conclusions -- References -- Leveraging Question Answering for Domain-Agnostic Information Extraction -- 1 Introduction -- 2 Related Work -- 3 Question Answering for Information Extraction -- 3.1 Models and Questions -- 3.2 Approach -- 3.3 Visual Explainability on Evaluation -- 4 Case Studies -- 4.1 Application to Toxicology Analysis -- 4.2 Application to Finance -- 5 Conclusion -- References -- Towards a Robust Solution for the Supermarket Shelf Audit Problem: Obsolete Price Tags in Shelves -- 1 Introduction -- 2 Dataset Collection -- 3 Proposed Approach -- 3.1 Image-to-Text Track -- 3.2 Localization Track -- 3.3 Selection Track -- 3.4 Report Generation -- 4 Results -- 5 Conclusions and Future Works.
References -- A Self-Organizing Map Clustering Approach to Support Territorial Zoning -- 1 Introduction -- 2 Related Work -- 2.1 Zoning with Self-Organizing Maps -- 2.2 Clustering Ordinal Categorical Data -- 3 Material and Methods -- 3.1 The Alto Taquari Basin - MS/MT, Brazil -- 3.2 Clustering Categorical Ordinal Data -- 3.3 Clustering Assessing -- 4 Results and Discussion -- 5 Conclusions -- References -- Spatial-Temporal Graph Transformer for Surgical Skill Assessment in Simulation Sessions -- 1 Introduction -- 2 Proposed Approach -- 2.1 Spectral Graph Convolutional Networks -- 2.2 Transformer Encoder -- 2.3 Surgical Skill Classifier -- 3 Experimental Results -- 3.1 Dataset -- 3.2 Data Preprocessing -- 3.3 Results -- 4 Conclusion -- References -- Deep Learning in the Identification of Psoriatic Skin Lesions -- 1 Introduction -- 2 Background and Literature Review -- 3 Methodology -- 3.1 Understanding the Problem -- 3.2 Deep Learning -- 3.3 Dataset -- 3.4 Classification Architectures -- 3.5 Training -- 4 Results -- 4.1 CLAHE -- 4.2 Type of Input Image -- 4.3 Data Augmentation -- 5 Discussion -- 6 Mobile Application -- 7 Conclusion -- References -- WildFruiP: Estimating Fruit Physicochemical Parameters from Images Captured in the Wild -- 1 Introduction -- 2 Related Work -- 2.1 Detection Methods -- 2.2 Segmentation Methods -- 2.3 Methods for Estimating Fruit Ripeness in Images -- 3 Proposed Method -- 3.1 Fruit Detection and Segmentation -- 3.2 Image Alignment -- 3.3 Determination of Physicochemical Parameters -- 4 Dataset -- 5 Experiments -- 5.1 Implementation Details -- 5.2 Metrics -- 5.3 Performance of the Proposed Approach -- 5.4 Impact of Alignment Phase -- 5.5 Impact of Model Architecture -- 5.6 Hard Samples -- 6 Conclusion and Future Work Prospects -- References.
Depression Detection Using Deep Learning and Natural Language Processing Techniques: A Comparative Study.
Record Nr. UNISA-996565865703316
Vasconcelos Verónica  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications : 26th Iberoamerican Congress, CIARP 2023, Coimbra, Portugal, November 27–30, 2023, Proceedings, Part I / / edited by Verónica Vasconcelos, Inês Domingues, Simão Paredes
Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications : 26th Iberoamerican Congress, CIARP 2023, Coimbra, Portugal, November 27–30, 2023, Proceedings, Part I / / edited by Verónica Vasconcelos, Inês Domingues, Simão Paredes
Autore Vasconcelos Verónica
Edizione [1st ed. 2024.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Descrizione fisica 1 online resource (764 pages)
Disciplina 006.4
Altri autori (Persone) DominguesInês
ParedesSimão
Collana Lecture Notes in Computer Science
Soggetto topico Pattern recognition systems
Machine learning
Computer vision
Computer engineering
Computer networks
Application software
Automated Pattern Recognition
Machine Learning
Computer Vision
Computer Engineering and Networks
Computer and Information Systems Applications
ISBN 3-031-49018-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents - Part I -- Contents - Part II -- Deblur Capsule Networks -- 1 Introduction -- 2 Related Works -- 3 Deblur Capsule Networks -- 3.1 Blur Type Classification -- 3.2 Point Spread Function Reconstruction -- 3.3 Image Deep Regularized Deconvolution -- 4 Experiments and Analysis -- 4.1 DbCN Optimization Procedure -- 4.2 Synthetic Camera Motion Blur -- 4.3 Synthetic Multi-domain Blur -- 4.4 Ablation Study -- 5 Conclusions and Future Works -- References -- Graph Embedding of Almost Constant Large Graphs -- 1 Introduction -- 2 Graphs and Graph Embedding -- 3 GraphFingerprint: An Embedding for Almost Constant Graphs -- 3.1 Algorithm Input Parameters -- 3.2 Local Substructures -- 3.3 GraphFingerprint Definition -- 3.4 GraphFingerprint Examples -- 4 Experimental Section -- 4.1 From Metal-Oxide Nanocompound to GraphFingerprint -- 4.2 Toxicity Prediction Based on Global Features -- 4.3 Toxicity Prediction Based on GraphFingerprints -- 4.4 Toxicity Prediction Based on Global Features and GraphFingerprints -- 5 Conclusions -- 6 Future Work -- References -- Feature Importance for Clustering -- 1 Introduction -- 2 Cluster Analysis -- 3 Proposed Methods -- 3.1 Prototype-Based Feature Importance -- 3.2 SHAP-Based Feature Importance -- 4 Experimental Simulations -- 5 Concluding Remarks -- References -- Uncovering Manipulated Files Using Mathematical Natural Laws -- 1 Introduction -- 2 Related Work -- 3 Benford's Law Fundamentals -- 3.1 Benford's Law Statement -- 4 Dataset -- 5 Benford's Law-Based Method -- 5.1 Pre-processing -- 5.2 Processing -- 5.3 Median Absolute Deviation -- 5.4 Evaluation Metrics -- 6 Results -- 6.1 Analysis of Results -- 7 Conclusions and Future Work -- References -- History Based Incremental Singular Value Decomposition for Background Initialization and Foreground Segmentation -- 1 Introduction.
2 Related Work -- 2.1 Identification of SFOs -- 2.2 Background Dependency -- 3 Methodology -- 3.1 Notation and Preliminaries -- 3.2 Computation of Incremental SVD -- 3.3 History Based Incremental SVD (hi-SVD) -- 4 Experimental Results -- 4.1 Datasets -- 4.2 SFO Status Identification Experiment -- 4.3 Foreground Segmentation Experiment -- 5 Conclusion -- References -- Vehicle Re-Identification Based on Unsupervised Domain Adaptation by Incremental Generation of Pseudo-Labels -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 DBSCAN Pseudo-Labels -- 3.2 Fine-Tuning -- 3.3 Unsupervised Domain Adaptation -- 4 Experimental Validation -- 4.1 Dataset and Evaluation Environment -- 4.2 Implementation Details -- 4.3 Ablation Study for Eps-Neighborhood in DBSCAN -- 4.4 Ablation Study for Increasing the Number of Cycles in the Generation of Pseudo-Labels -- 5 Conclusions -- References -- How to Turn Your Camera into a Perfect Pinhole Model -- 1 Introduction -- 2 Methods -- 2.1 Gaussian Processes -- 2.2 Constructing an Ideal Pinhole Camera -- 2.3 The Datasets -- 3 Results -- 3.1 Collineation Assumption -- 3.2 Reprojection Error -- 3.3 Distortion Removal -- 4 Discussion -- 5 Conclusion -- A Zhang's Method -- B Simplified Zhang's Method -- References -- Single Image HDR Synthesis with Histogram Learning -- 1 Introduction -- 2 Method -- 2.1 LDR2EDR by Histogram and Resolution difference -- 2.2 EDR2HDR by Cumulative Histogram Learning -- 2.3 Fine-Tuning with Reinforcement Learning -- 3 Experiments -- 4 Conclusion -- References -- But That's Not Why: Inference Adjustment by Interactive Prototype Revision -- 1 Introduction -- 2 Prototype-Based Learning -- 3 Interactive Prototype Revision -- 4 Results -- 5 Conclusion -- References -- Teaching Practices Analysis Through Audio Signal Processing -- 1 Introduction -- 2 Related Work -- 3 Dataset Description.
4 Classroom Activity Detection -- 4.1 Training and Testing Data -- 4.2 Unsupervised Diarization Approach -- 4.3 Supervised Audio Classification -- 4.4 Experiments and Results -- 5 Additional Tools for English Lessons Analysis -- 5.1 Language Detection -- 5.2 Key Phrases Matching -- 5.3 User Interface for Education Technicians -- 6 Conclusions and Further Work -- References -- Time Distributed Multiview Representation for Speech Emotion Recognition -- 1 Introduction -- 2 Related Work -- 3 Proposed Strategy -- 3.1 Database Description -- 3.2 General Architecture -- 3.3 Step 1 - Initial Procedures -- 3.4 Steps 2 and 3 - Algorithms and Combiner -- 3.5 Steps 4 and 5 - LSTM and Emotion Classification -- 4 Experimental Results -- 4.1 Experiment 1 - Results for All RAVDESS Database -- 4.2 Experiment 2 - Database Divided by Intensity -- 4.3 Experiment 3 - LOSO Protocol -- 5 Discussions -- 6 Conclusion -- References -- Detection of Covid-19 in Chest X-Ray Images Using Percolation Features and Hermite Polynomial Classification -- 1 Introduction -- 2 Materials and Methods -- 2.1 Image Database -- 2.2 Methodology -- 3 Results and Discussion -- 3.1 Feature Evaluation -- 3.2 Performance of the HP Classifier -- 4 Conclusion -- References -- Abandoned Object Detection Using Persistent Homology -- 1 Introduction -- 2 From Background Subtraction to Simplicial Complex -- 3 Surveillance Points -- 4 Filtration -- 5 Persistent Homology and Topological Signature -- 6 Detecting Abandoned Objects -- 7 Experimental Results -- 8 Conclusion and Future Works -- References -- Interactive Segmentation with Incremental Watershed Cuts -- 1 Introduction -- 2 Watershed Cuts -- 3 Semi-supervised Watershed Cut Algorithm with Interactions -- 3.1 Tree-Node Marking -- 3.2 Pixel Labeling -- 3.3 Incremental Workflow -- 4 Experiments -- 4.1 Experiment with User Generated Seeds.
4.2 Experiment with Randomly Generated Seeds -- 5 Conclusion -- References -- Supervised Learning of Hierarchical Image Segmentation -- 1 Introduction -- 2 Ultrametric Dataset -- 3 Model -- 4 Evaluation Metrics -- 5 Experiments -- 6 Conclusion -- References -- Unveiling the Influence of Image Super-Resolution on Aerial Scene Classification -- 1 Introduction -- 2 Super-Resolution -- 2.1 Super-Resolution Convolution Neural Network (SRCNN) -- 2.2 Modified 3D Residual-in-Residual Dense Block (m3DRRDB) -- 2.3 SwinIR Transformer -- 3 Scene Classification -- 4 Experiments -- 4.1 Datasets -- 4.2 Experimental Settings -- 5 Results and Discussion -- 5.1 Experiment 1: Ranking of Super-Resolution Methods -- 5.2 Experiment 2: Impact of Super-Resolution on Aerial Scene Classification -- 6 Conclusion -- References -- Weeds Classification with Deep Learning: An Investigation Using CNN, Vision Transformers, Pyramid Vision Transformers, and Ensemble Strategy -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Datasets -- 3.2 Models -- 3.3 Ensemble -- 3.4 Evaluation -- 3.5 Training Configuration -- 3.6 Execution Environment -- 4 Results and Discussion -- 5 Conclusions -- References -- Leveraging Question Answering for Domain-Agnostic Information Extraction -- 1 Introduction -- 2 Related Work -- 3 Question Answering for Information Extraction -- 3.1 Models and Questions -- 3.2 Approach -- 3.3 Visual Explainability on Evaluation -- 4 Case Studies -- 4.1 Application to Toxicology Analysis -- 4.2 Application to Finance -- 5 Conclusion -- References -- Towards a Robust Solution for the Supermarket Shelf Audit Problem: Obsolete Price Tags in Shelves -- 1 Introduction -- 2 Dataset Collection -- 3 Proposed Approach -- 3.1 Image-to-Text Track -- 3.2 Localization Track -- 3.3 Selection Track -- 3.4 Report Generation -- 4 Results -- 5 Conclusions and Future Works.
References -- A Self-Organizing Map Clustering Approach to Support Territorial Zoning -- 1 Introduction -- 2 Related Work -- 2.1 Zoning with Self-Organizing Maps -- 2.2 Clustering Ordinal Categorical Data -- 3 Material and Methods -- 3.1 The Alto Taquari Basin - MS/MT, Brazil -- 3.2 Clustering Categorical Ordinal Data -- 3.3 Clustering Assessing -- 4 Results and Discussion -- 5 Conclusions -- References -- Spatial-Temporal Graph Transformer for Surgical Skill Assessment in Simulation Sessions -- 1 Introduction -- 2 Proposed Approach -- 2.1 Spectral Graph Convolutional Networks -- 2.2 Transformer Encoder -- 2.3 Surgical Skill Classifier -- 3 Experimental Results -- 3.1 Dataset -- 3.2 Data Preprocessing -- 3.3 Results -- 4 Conclusion -- References -- Deep Learning in the Identification of Psoriatic Skin Lesions -- 1 Introduction -- 2 Background and Literature Review -- 3 Methodology -- 3.1 Understanding the Problem -- 3.2 Deep Learning -- 3.3 Dataset -- 3.4 Classification Architectures -- 3.5 Training -- 4 Results -- 4.1 CLAHE -- 4.2 Type of Input Image -- 4.3 Data Augmentation -- 5 Discussion -- 6 Mobile Application -- 7 Conclusion -- References -- WildFruiP: Estimating Fruit Physicochemical Parameters from Images Captured in the Wild -- 1 Introduction -- 2 Related Work -- 2.1 Detection Methods -- 2.2 Segmentation Methods -- 2.3 Methods for Estimating Fruit Ripeness in Images -- 3 Proposed Method -- 3.1 Fruit Detection and Segmentation -- 3.2 Image Alignment -- 3.3 Determination of Physicochemical Parameters -- 4 Dataset -- 5 Experiments -- 5.1 Implementation Details -- 5.2 Metrics -- 5.3 Performance of the Proposed Approach -- 5.4 Impact of Alignment Phase -- 5.5 Impact of Model Architecture -- 5.6 Hard Samples -- 6 Conclusion and Future Work Prospects -- References.
Depression Detection Using Deep Learning and Natural Language Processing Techniques: A Comparative Study.
Record Nr. UNINA-9910766892403321
Vasconcelos Verónica  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui