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ICDSC : fourth ACM/IEEE International Conference on Distributed Smart Cameras, August 31st-September 4th, 2010, Atlanta, GA, USA
| ICDSC : fourth ACM/IEEE International Conference on Distributed Smart Cameras, August 31st-September 4th, 2010, Atlanta, GA, USA |
| Autore | Wolf Marilyn |
| Pubbl/distr/stampa | [Place of publication not identified], : ACM, 2010 |
| Descrizione fisica | 1 online resource (252 pages) |
| Collana | ACM Conferences |
| Soggetto topico |
Engineering & Applied Sciences
Applied Physics |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti |
International Conference on Distributed Smart Cameras : fourth Association for Computing Machinery/Institute of Electrical and Electronics Engineers International Conference on Distributed Smart Cameras, August 31st-September 4th, 2010, Atlanta, Georgia, United States
Proceedings of the Fourth ACM/IEEE International Conference on Distributed Smart Cameras ICDSC '10 International Conference on Distributed Smart Cameras, Atlanta, GA, USA - August 31 - September 04, 2010 |
| Record Nr. | UNINA-9910376010903321 |
Wolf Marilyn
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| [Place of publication not identified], : ACM, 2010 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Image Analysis and Processing - ICIAP 2023 Workshops : 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 : Udine, Italy, September 11–15, 2023, Proceedings, Part II / / edited by Gian Luca Foresti, Andrea Fusiello, Edwin Hancock |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (514 pages) |
| Disciplina | 354.81150006 |
| 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 |
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Image Analysis and Processing -- ICIAP 2011 [[electronic resource] ] : 16th International Conference, Ravenna, Italy, September 14-16, 2011, Proceedings, Part II / / edited by Giuseppe Maino, Gian Luca Foresti
| Image Analysis and Processing -- ICIAP 2011 [[electronic resource] ] : 16th International Conference, Ravenna, Italy, September 14-16, 2011, Proceedings, Part II / / edited by Giuseppe Maino, Gian Luca Foresti |
| Edizione | [1st ed. 2011.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2011 |
| Descrizione fisica | 1 online resource (XXIII, 500 p.) |
| Disciplina | 006.4 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Pattern recognition
Optical data processing Artificial intelligence Computer graphics Algorithms Pattern Recognition Image Processing and Computer Vision Artificial Intelligence Computer Graphics Algorithm Analysis and Problem Complexity |
| ISBN | 3-642-24088-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996465439703316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2011 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Image Analysis and Processing -- ICIAP 2011 [[electronic resource] ] : 16th International Conference, Ravenna, Italy, September 14-16, 2011, Proceedings, Part I / / edited by Giuseppe Maino, Gian Luca Foresti
| Image Analysis and Processing -- ICIAP 2011 [[electronic resource] ] : 16th International Conference, Ravenna, Italy, September 14-16, 2011, Proceedings, Part I / / edited by Giuseppe Maino, Gian Luca Foresti |
| Edizione | [1st ed. 2011.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2011 |
| Descrizione fisica | 1 online resource (XXIII, 714 p. 343 illus., 223 illus. in color.) |
| Disciplina | 621.36/7 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Pattern recognition
Optical data processing Artificial intelligence Computer graphics Algorithms Pattern Recognition Image Processing and Computer Vision Artificial Intelligence Computer Graphics Algorithm Analysis and Problem Complexity |
| ISBN | 3-642-24085-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996465937603316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2011 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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