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Advances in visual computing : 17th International Symposium, ISVC 2022, San Diego, CA, USA, October 3-5, 2022, proceedings, part II. / / edited by George Bebis, [and eight others]
Advances in visual computing : 17th International Symposium, ISVC 2022, San Diego, CA, USA, October 3-5, 2022, proceedings, part II. / / edited by George Bebis, [and eight others]
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2022]
Descrizione fisica 1 online resource (466 pages)
Disciplina 929.605
Collana Lecture Notes in Computer Science
Soggetto topico Computer vision
ISBN 3-031-20716-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Keynote Talks -- Towards Scaling Up GANs -- Sensible Machine Learning for Geometry -- Designing Augmented Reality for the Future of Work -- The Future of Visual Computing via Foundation Models (Banquet Keynote Talk) -- 3D Reconstruction: Leveraging Synthetic Data for Lightweight Reconstruction -- Human-AI Interaction in Visual Analytics: Designing for the "Two Black Boxes" Problem -- Contents - Part II -- Contents - Part I -- ST: Neuro-inspired Artificial Intelligence -- Brain Shape Correspondence Analysis Using Functional Maps -- 1 Introduction -- 2 Materials and Methods -- 2.1 Database -- 2.2 Methodology -- 3 Results -- 3.1 First Experiment -- 3.2 Second Experiment -- 3.3 Third Experiment -- 4 Conclusions -- References -- Biomimetic Oculomotor Control with Spiking Neural Networks -- 1 Introduction -- 2 Related Work -- 3 Eye Model and Neuromuscular Oculomotor Controller -- 4 Spiking Neurons -- 4.1 Encoding the Input Signals -- 4.2 Outputs -- 5 The SLiNet Model -- 5.1 Architecture -- 5.2 Training -- 6 Experiments -- 6.1 Eye Movements -- 6.2 Comparison to Human Eye Movements -- 7 Conclusions -- References -- Border Ownership, Category Selectivity and Beyond -- 1 Introduction -- 2 Implementation -- 2.1 Border-Ownership Coding Method -- 2.2 Category-Selective Coding Method -- 2.3 TcNet -- 3 Results -- 3.1 Datasets -- 3.2 Statistic Evaluation Criteria -- 4 Discussion -- 4.1 T-Junctions and Other 'KEY' Points -- 4.2 Global Context Awareness -- 4.3 Early Object Representation, 'PRoto-Object' -- 4.4 Relation to Biological Vision Systems -- 5 Summary -- References -- Sparse Kernel Transfer Learning -- 1 Introduction -- 2 Background -- 2.1 Background in Convolutional Neural Networks -- 2.2 Background in Sparse Coding -- 3 Methodology -- 3.1 Dictionary Learning -- 3.2 Initialization Techniques -- 3.3 Datasets.
3.4 Kernel Transfer Learning -- 4 Experiments and Results -- 4.1 Comparison with Other Initialization Methods -- 4.2 Learning with Less Labels -- 4.3 Breast Cancer Detection -- 4.4 Intepretability and Complexity -- 5 Conclusion -- References -- Applications -- Photobombing Removal Benchmarking -- 1 Introduction -- 2 Related Work -- 2.1 Traditional Methods -- 2.2 Deep Learning-based Methods -- 3 Photobombing Removal Benchmark -- 3.1 Benchmarking Dataset -- 3.2 Benchmarking Methods -- 4 Experiments -- 4.1 Performance Metrics -- 4.2 Experimental Results -- 5 Conclusion and Future Works -- References -- Automatic Detection and Recognition of Products and Planogram Conformity Analysis in Real Time on Store Shelves -- 1 Introduction -- 1.1 Features for Detection of Retails Products -- 1.2 Detection of Single Product -- 2 Clustering by Products Famillies -- 2.1 Multi-object Detection with ASIFT -- 2.2 Distance Normalisation -- 2.3 DBSCAN: Products Famillies -- 2.4 Shelf Planogram Conformity Rate -- 3 Experiments -- 3.1 Database -- 3.2 Evaluation Metrics -- 4 Conclusion -- References -- Enhancing Privacy in Computer Vision Applications: An Emotion Preserving Approach to Obfuscate Faces -- 1 Introduction -- 2 Related Work -- 3 Approach -- 3.1 Face Detection -- 3.2 Face Selection -- 3.3 Face Reconstruction -- 3.4 Color Adaptation -- 3.5 Cloning -- 4 Validation -- 4.1 Experiment -- 4.2 Results -- 5 Conclusion and Future Work -- References -- House Price Prediction via Visual Cues and Estate Attributes -- 1 Introduction -- 2 Related Work -- 3 Proposed Work -- 3.1 Data Collection -- 3.2 Computational Model -- 4 Experiments -- 4.1 Evaluation Metrics -- 4.2 Experimental Results -- 4.3 Ablation Studies -- 5 Conclusion and Future Works -- References -- DRB-Net: Dilated Residual Block Network for Infrared Image Restoration -- 1 Introduction -- 2 Related Work.
2.1 Non-learning Denoising Methods -- 2.2 Discriminative Learning Denoising Methods -- 2.3 Deep Learning for IR Imaging -- 3 Proposed Architecture -- 3.1 Why Dilated Convolution? -- 3.2 Residual Blocks -- 3.3 Architecture and Compared Methods -- 4 Dataset -- 4.1 Sample Preparation and Image Acquisition -- 4.2 Dataset Creation -- 4.3 Implementation -- 5 Experiments -- 5.1 DRB-Net Specification -- 5.2 Denoising of Synthetic Noisy Data -- 5.3 Generalization and Robustness Test -- 6 Conclusion and Future Work -- References -- Segmentation and Tracking -- Saliency Can Be All You Need in Contrastive Self-supervised Learning -- 1 Introduction -- 2 Motivation and Background -- 2.1 Related Work -- 2.2 Concrete Background -- 3 Implementation, Setup and Results -- 3.1 Setup and Datasets -- 3.2 Preliminary: Running SGD on NORCE-PV and MultiRes-PV Datasets -- 3.3 An Efficient Implementation -- 3.4 Using SGD as an Augmentation Policy in Contrastive SSL Algorithms -- 4 Discussion -- 5 Conclusions -- References -- GCEENet: A Global Context Enhancement and Exploitation for Medical Image Segmentation -- 1 Introduction -- 2 Related Work -- 2.1 Convolutional Neural Networks for Semantic Segmentation -- 2.2 Contextual Information Modeling -- 3 Proposed Architecture -- 3.1 Overview -- 3.2 Global Context Encoder Module -- 3.3 Local Distribution -- 3.4 Aggregator Module -- 3.5 Loss Function -- 4 Experiments and Discussion -- 4.1 Benchmark Datasets -- 4.2 Experiment Settings -- 5 Results and Discussion -- 5.1 Ablation Study -- 5.2 Comparison to Baseline Models -- 6 Conclusion -- References -- V2F: Real Time Video Segmentation with Apache Flink -- 1 Introduction -- 2 Related Work -- 3 Video2Flink Architecture -- 3.1 V2F Operators -- 4 Experiments -- 5 Conclusions and Future Work -- References -- Joint Discriminative and Metric Embedding Learning for Person Re-identification.
1 Introduction -- 2 Related Work -- 3 Proposed Approach -- 3.1 Classification Losses -- 3.2 Metric Learning Loss -- 3.3 Joint Classification and Metric Loss -- 3.4 Network Architecture -- 4 Experiments -- 4.1 Implementation Details -- 4.2 Comparison with State-of-the-Art Methods -- 4.3 Ablation Study -- 5 Conclusions -- References -- Transformer Networks for Future Person Localization in First-Person Videos -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Problem Overview -- 3.2 Input Overview -- 3.3 Implementation Details -- 4 Experiments -- 4.1 Evaluation Metrics and Baselines -- 4.2 Quantitative Results -- 4.3 Additional Analysis -- 4.4 Inference Time Analysis -- 5 Conclusion -- References -- Virtual Reality -- VR-SFT: Reproducing Swinging Flashlight Test in Virtual Reality to Detect Relative Afferent Pupillary Defect -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Swinging Flashlight Test in Virtual Reality -- 3.2 VR Implementation and Experimental Software -- 3.3 RAPD Scoring -- 4 Dataset -- 5 Data Analysis and Results -- 6 Discussion and Future Work -- References -- A Quantitative Analysis of Redirected Walking in Virtual Reality Using Saccadic Eye Movements -- 1 Introduction -- 2 Methodology -- 2.1 Simulation and Hardware -- 2.2 Simulation Tasks and Data Collection -- 2.3 Eye Tracking -- 2.4 Questionnaire -- 2.5 Demographics -- 3 Results -- 4 Conclusion and Future Work -- References -- A DirectX-Based DICOM Viewer for Multi-user Surgical Planning in Augmented Reality -- 1 Introduction -- 2 Related Work -- 2.1 Holographic DICOM Viewer Prototypes -- 2.2 Interaction with 3D Objects -- 3 System Design Overview -- 4 Direct3D-Based DICOM Viewer Implementation -- 4.1 Smartphones as User Input Devices -- 4.2 Functionalities -- 4.3 Marker-Based 3D Object Placement -- 5 User Interactions -- 5.1 Virtual 2D Plane Touch.
5.2 3D User Interaction -- 6 Experiments -- 7 Conclusions -- References -- Virtual-Reality Based Vestibular Ocular Motor Screening for Concussion Detection Using Machine-Learning -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Naive Bayes -- 3.2 Decision Tree -- 3.3 Random Forest -- 3.4 Support Vector Classifer -- 3.5 AdaBoost -- 3.6 Gaussian Process Classifier -- 3.7 Logistic Regression -- 3.8 Perceptron -- 3.9 Isolation Forest -- 3.10 One Class SVM -- 4 Experimental Analysis -- 4.1 Data Collection Using Virtual-Reality Headset -- 4.2 Data Splitting for Training and Testing -- 4.3 Qualitative Evaluation -- 4.4 Quantitative Evaluation -- 5 Conclusion -- References -- Posters -- GUILD - A Generator for Usable Images in Large-Scale Datasets -- 1 Introduction -- 2 Related Work -- 2.1 Manual Collection of Datasets -- 2.2 Synthetic Generation of Datasets -- 3 Implementation -- 3.1 Approach -- 3.2 Object Models -- 3.3 Environments -- 3.4 Label Generation -- 4 Evaluation -- 4.1 Evaluation Design -- 4.2 Evaluation Datasets -- 4.3 Accuracy -- 4.4 Generalizability -- 4.5 Variety -- 5 Conclusion and Future Work -- References -- Distributional Semantics of Line Charts for Trend Classification -- 1 Introduction -- 2 Dataset -- 3 Related Work -- 3.1 Information Graphic Description Generation -- 3.2 Prototype Learning -- 3.3 Bag of Words for Computer Vision -- 3.4 Distributional Semantics -- 4 Architecture and Methodology -- 4.1 Forming the Vocabulary -- 4.2 Line Chart Embeddings -- 4.3 Classification -- 5 Implementation -- 6 Experiments and Results -- 6.1 Classification Task -- 6.2 Results -- 7 Discussion -- 8 Conclusion -- References -- Deep Learning Hyperparameter Optimization for Breast Mass Detection in Mammograms -- 1 Introduction -- 2 Background and Motivation -- 2.1 End-to-End Pipeline -- 2.2 Genetic Algorithm -- 2.3 Binary Tournament Selection.
2.4 Simulated Binary Crossover (SBX).
Record Nr. UNISA-996503470203316
Cham, Switzerland : , : Springer, , [2022]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Advances in visual computing : 17th international symposium, ISVC 2022, San Diego, CA, USA, October 3-5, 2022, proceedings, part I / / edited by George Bebis [and eight others]
Advances in visual computing : 17th international symposium, ISVC 2022, San Diego, CA, USA, October 3-5, 2022, proceedings, part I / / edited by George Bebis [and eight others]
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2022]
Descrizione fisica 1 online resource (486 pages)
Disciplina 929.605
Collana Lecture Notes in Computer Science
Soggetto topico Computers
ISBN 3-031-20713-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Keynote Talks -- Towards Scaling Up GANs -- Sensible Machine Learning for Geometry -- Designing Augmented Reality for the Future of Work -- The Future of Visual Computing via Foundation Models (Banquet Keynote Talk) -- 3D Reconstruction: Leveraging Synthetic Data for Lightweight Reconstruction -- Human-AI Interaction in Visual Analytics: Designing for the "Two Black Boxes" Problem -- Contents - Part I -- Contents - Part II -- Deep Learning I -- Unsupervised Structure-Consistent Image-to-Image Translation -- 1 Introduction -- 2 Background and Related Work -- 3 Method -- 3.1 Encoder -- 3.2 Generator -- 3.3 Structure and Texture Disentanglement -- 3.4 Objective Function -- 4 Experiments -- 4.1 Comparison to State-of-the-Art -- 5 Applications -- 5.1 Addressing Bias in Training Datasets -- 5.2 Training Datasets for Semantic Segmentation of Satellite Images -- 6 Discussion and Limitations -- 7 Conclusions -- References -- Learning Representations for Masked Facial Recovery -- 1 Introduction -- 2 Relevant Works -- 3 Method -- 3.1 Baseline Model -- 3.2 Unmasking Model -- 3.3 Datasets -- 3.4 Implementation Details -- 4 Experimental Results -- 5 Conclusions -- References -- Deep Learning Based Shrimp Classification -- 1 Introduction -- 2 Related Work -- 3 Proposed Approach -- 3.1 Acquisition -- 3.2 Preprocessing -- 3.3 Classification -- 4 Experimental Results -- 5 Conclusions -- References -- Gait Emotion Recognition Using a Bi-modal Deep Neural Network -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 4 Experimental Results -- 5 Conclusion and Future Work -- References -- Attacking Frequency Information with Enhanced Adversarial Networks to Generate Adversarial Samples -- 1 Introduction -- 2 Related Work -- 2.1 Adversarial Samples -- 2.2 Black-Box Attacks -- 2.3 Frequency Features and Attacks.
3 Our Frequency Attack Approach -- 3.1 Separate High and Low Frequency Information -- 3.2 Dual Discriminators Support Attack -- 3.3 Frequency Attack Framework -- 3.4 Network Architecture -- 3.5 Loss Function -- 4 Experiments -- 4.1 Evaluation Metric -- 4.2 Ablation Study -- 4.3 Transferability of FAF -- 4.4 Attack Under Defenses -- 5 Conclusion -- References -- Visualization -- Explainable Interactive Projections for Image Data -- 1 Introduction -- 2 Related Work -- 2.1 Interactive Dimensionality Reduction -- 2.2 Semantic Interaction -- 2.3 Explainability in Deep Learning -- 3 Tasks -- 3.1 Define Custom Similarities Based on Prior Knowledge -- 3.2 Link Human and Machine Defined Similarities -- 4 Workflow and Methodology -- 4.1 Initial State -- 4.2 Interactions and Inverse Projection -- 4.3 Visual Explanations -- 5 Usage Scenario: Edamame Pods -- 6 Discussion -- 7 Conclusion -- References -- MultiProjector: Temporal Projection for Multivariates Time Series -- 1 Introduction -- 2 Related Work -- 2.1 Visualizing High Dimensional Temporal Datasets -- 2.2 Dimension Reduction -- 3 Methodology -- 3.1 Clusterings -- 3.2 Multidimensional Projections -- 3.3 Visualizing the Time Dimension -- 3.4 Multivariate Representations -- 4 Use Cases -- 4.1 Use Case 1: Monthly US Employment Rate -- 4.2 Use Case 2: Monitoring Computer Metrics -- 4.3 Use Case 3: Plant Genetics -- 4.4 Discussion -- 5 Conclusion -- References -- Deep Learning Based Super-Resolution for Medical Volume Visualization with Direct Volume Rendering -- 1 Introduction -- 2 Related Work -- 2.1 Image and Video Super-resolution -- 2.2 Resolution Enhancement for Rendered Content -- 3 Methodology -- 3.1 Direct Volume Rendering Framework -- 3.2 Network Architecture -- 4 Dataset -- 5 Evaluation -- 5.1 Performance Gain with Additional Feature at the Input.
5.2 Performance Gain with Additional Previous Frames -- 5.3 Upsampling Ratio -- 6 Conclusion and Future Work -- References -- Interactive Virtual Reality Exploration of Large-Scale Datasets Using Omnidirectional Stereo Images -- 1 Introduction -- 2 Related Work -- 2.1 Image-Based Visualization -- 2.2 Virtual Reality for Large-Scale Data Sets -- 3 Science Drivers -- 3.1 Cancer Cell Transport -- 3.2 Graphene Superlubricity -- 4 Cinema ODS Image Database -- 4.1 Rendering -- 5 Interactive Cinema ODS Viewer -- 6 Evaluation -- 6.1 Visualization Latency -- 6.2 VR Frame Rate -- 6.3 Qualitative Feedback -- 7 Conclusion -- References -- A Quantitative Analysis of Labeling Issues in the CelebA Dataset -- 1 Introduction -- 2 Related Work -- 3 Incorrect Labels -- 3.1 Contradicting and Conflicting Labels -- 3.2 Mislabeling -- 4 Inconsistent Labels -- 4.1 Consistency -- 4.2 Agreement -- 4.3 Correlated Labels -- 5 Conclusion -- References -- Object Detection and Recognition -- Recognition of Aquatic Invasive Species Larvae Using Autoencoder-Based Feature Averaging -- 1 Introduction -- 2 Related Work -- 2.1 Aquatic Invasive Species -- 2.2 Local Responses to Aquatic Invasive Species -- 2.3 Classification with Image Sets -- 2.4 Underwater Image Classification -- 2.5 Autoencoders -- 3 Methodology -- 3.1 Solution Description -- 3.2 Convolutional Autoencoder -- 3.3 Classification Model -- 3.4 Activation Functions -- 3.5 Loss Functions -- 3.6 Base Model -- 3.7 Dataset -- 4 Results -- 4.1 Evaluation Metric -- 4.2 Quantitative Analysis -- 4.3 Comparative Analysis -- 5 Conclusion -- References -- Subspace Analysis for Multi-temporal Disaster Mapping Using Satellite Imagery -- 1 Introduction -- 2 Subspace Learning-Based Disaster Mapping -- 2.1 Region Delineation -- 2.2 Segmentation Fusion -- 2.3 Subspace Learning for Disaster Mapping.
3 Determining the Changed and Unchanged Regions -- 4 Experiments, Results and Discussion -- 4.1 Experimental Setup -- 4.2 Results and Discussion -- 5 Conclusion -- References -- Open-Set Plankton Recognition Using Similarity Learning -- 1 Introduction -- 2 Related Work -- 2.1 Plankton Recognition -- 2.2 Open-Set Classification -- 2.3 Classification by Metric Learning -- 3 Proposed Method -- 3.1 Angular Margin Loss -- 4 Experiments -- 4.1 Data -- 4.2 Description of Experiments -- 4.3 Results -- 5 Conclusions -- References -- Sensor Fusion Operators for Multimodal 2D Object Detection -- 1 Introduction -- 2 Related Work -- 3 Camera-LiDAR 2D Object Detector -- 4 Sensor Fusion Operators -- 5 Experimental Results -- 5.1 Experimental Setting -- 5.2 Evaluation of Early Sensor Fusion -- 5.3 Evaluation of Mid-Level Sensor Fusion -- 5.4 Complexity Analysis -- 6 Conclusion -- References -- Learning When to Say ``I Don't Know -- 1 Introduction -- 2 Preliminaries -- 3 Related Work -- 4 Proposed Method -- 5 Experiments -- 5.1 Synthetic Data -- 5.2 Image Datasets -- 5.3 Text Datasets -- 5.4 Generalization from Validation to Test Data -- 5.5 Alternative Confidence Interval Formulations -- 5.6 Discussion -- 6 Conclusion -- References -- Multi-class Detection and Tracking of Intracorporeal Suturing Instruments in an FLS Laparoscopic Box Trainer Using Scaled-YOLOv4 -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Scaled-YOLOv4 Architecture -- 3.2 Measurement Algorithm -- 4 Experimental Setup -- 4.1 Dataset -- 4.2 Software Implementation -- 5 Results -- 6 Discussion -- 7 Conclusion and Future Work -- References -- Deep Learning II -- A New Approach to Visual Classification Using Concatenated Deep Learning for Multimode Fusion of EEG and Image Data -- 1 Introduction -- 2 Related Work -- 3 Datasets -- 3.1 EEG-ImageNet.
3.2 Visual Stimuli EEG Dataset: Real-World 3D Objects and Corresponding 2D Image Stimuli -- 4 Data Encoding and Processing -- 4.1 Classical Feature Extraction for EEG Data -- 4.2 Classical Feature Extraction for Image Data -- 4.3 Principal Component Analysis (PCA) Encoding -- 4.4 Grayscale-Image Encoding for EEG Data -- 5 Methods and Model Implementation -- 5.1 Conventional Machine Learning Classifiers -- 5.2 LSTM-Based EEG Model (LEM) ch17ourvisclasspaper -- 5.3 CNN-Based Image Model (CIM) ch17ourvisclasspaper -- 5.4 Grayscale-Image Encoded EEG Model (GEM) -- 5.5 Concatenation-Based Models ch17ourvisclasspaper -- 6 Experiments and Results -- 6.1 Baseline Visual Classification for EEG and Image Data -- 6.2 Classification Using Deep Learning Models -- 6.3 Hemispherical Brain Region Classification Comparison -- 6.4 Visual Classification Using Multimodal Deep Learning -- 6.5 Visual Classification for Real Object Versus Image as Stimuli -- 7 Discussion -- 8 Conclusion -- References -- Deep Learning-Based Classification of Plant Xylem Tissue from Light Micrographs -- 1 Introduction -- 2 Related Works -- 3 Dataset and Problem Definition -- 4 Methodology -- 4.1 Data Augmentation and Pre-processing -- 4.2 Cascading-Like Model -- 4.3 Global Contextualization Approach -- 5 Experiments and Results -- 5.1 Model Evaluation Metric -- 5.2 Baseline Results -- 5.3 Results -- 6 Discussion -- 7 Conclusion -- References -- VampNet: Unsupervised Vampirizing of Convolutional Networks -- 1 Introduction -- 2 Related Work -- 2.1 Correlation-Based Feature Map Analysis -- 2.2 Multitask Neural Networks -- 2.3 Networks Merging -- 3 Method -- 3.1 Linearity Between Feature Maps -- 3.2 Ranking Linearity Between Features -- 3.3 Vampirizing a Feature Using a Convolutional Operator -- 3.4 Vampirizing a Layer -- 3.5 Automatic Selection of the Layer to Be Replaced -- 4 Experiments.
4.1 Setup.
Record Nr. UNINA-9910634049103321
Cham, Switzerland : , : Springer, , [2022]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Advances in visual computing : 17th International Symposium, ISVC 2022, San Diego, CA, USA, October 3-5, 2022, proceedings, part II. / / edited by George Bebis, [and eight others]
Advances in visual computing : 17th International Symposium, ISVC 2022, San Diego, CA, USA, October 3-5, 2022, proceedings, part II. / / edited by George Bebis, [and eight others]
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2022]
Descrizione fisica 1 online resource (466 pages)
Disciplina 929.605
Collana Lecture Notes in Computer Science
Soggetto topico Computer vision
ISBN 3-031-20716-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Keynote Talks -- Towards Scaling Up GANs -- Sensible Machine Learning for Geometry -- Designing Augmented Reality for the Future of Work -- The Future of Visual Computing via Foundation Models (Banquet Keynote Talk) -- 3D Reconstruction: Leveraging Synthetic Data for Lightweight Reconstruction -- Human-AI Interaction in Visual Analytics: Designing for the "Two Black Boxes" Problem -- Contents - Part II -- Contents - Part I -- ST: Neuro-inspired Artificial Intelligence -- Brain Shape Correspondence Analysis Using Functional Maps -- 1 Introduction -- 2 Materials and Methods -- 2.1 Database -- 2.2 Methodology -- 3 Results -- 3.1 First Experiment -- 3.2 Second Experiment -- 3.3 Third Experiment -- 4 Conclusions -- References -- Biomimetic Oculomotor Control with Spiking Neural Networks -- 1 Introduction -- 2 Related Work -- 3 Eye Model and Neuromuscular Oculomotor Controller -- 4 Spiking Neurons -- 4.1 Encoding the Input Signals -- 4.2 Outputs -- 5 The SLiNet Model -- 5.1 Architecture -- 5.2 Training -- 6 Experiments -- 6.1 Eye Movements -- 6.2 Comparison to Human Eye Movements -- 7 Conclusions -- References -- Border Ownership, Category Selectivity and Beyond -- 1 Introduction -- 2 Implementation -- 2.1 Border-Ownership Coding Method -- 2.2 Category-Selective Coding Method -- 2.3 TcNet -- 3 Results -- 3.1 Datasets -- 3.2 Statistic Evaluation Criteria -- 4 Discussion -- 4.1 T-Junctions and Other 'KEY' Points -- 4.2 Global Context Awareness -- 4.3 Early Object Representation, 'PRoto-Object' -- 4.4 Relation to Biological Vision Systems -- 5 Summary -- References -- Sparse Kernel Transfer Learning -- 1 Introduction -- 2 Background -- 2.1 Background in Convolutional Neural Networks -- 2.2 Background in Sparse Coding -- 3 Methodology -- 3.1 Dictionary Learning -- 3.2 Initialization Techniques -- 3.3 Datasets.
3.4 Kernel Transfer Learning -- 4 Experiments and Results -- 4.1 Comparison with Other Initialization Methods -- 4.2 Learning with Less Labels -- 4.3 Breast Cancer Detection -- 4.4 Intepretability and Complexity -- 5 Conclusion -- References -- Applications -- Photobombing Removal Benchmarking -- 1 Introduction -- 2 Related Work -- 2.1 Traditional Methods -- 2.2 Deep Learning-based Methods -- 3 Photobombing Removal Benchmark -- 3.1 Benchmarking Dataset -- 3.2 Benchmarking Methods -- 4 Experiments -- 4.1 Performance Metrics -- 4.2 Experimental Results -- 5 Conclusion and Future Works -- References -- Automatic Detection and Recognition of Products and Planogram Conformity Analysis in Real Time on Store Shelves -- 1 Introduction -- 1.1 Features for Detection of Retails Products -- 1.2 Detection of Single Product -- 2 Clustering by Products Famillies -- 2.1 Multi-object Detection with ASIFT -- 2.2 Distance Normalisation -- 2.3 DBSCAN: Products Famillies -- 2.4 Shelf Planogram Conformity Rate -- 3 Experiments -- 3.1 Database -- 3.2 Evaluation Metrics -- 4 Conclusion -- References -- Enhancing Privacy in Computer Vision Applications: An Emotion Preserving Approach to Obfuscate Faces -- 1 Introduction -- 2 Related Work -- 3 Approach -- 3.1 Face Detection -- 3.2 Face Selection -- 3.3 Face Reconstruction -- 3.4 Color Adaptation -- 3.5 Cloning -- 4 Validation -- 4.1 Experiment -- 4.2 Results -- 5 Conclusion and Future Work -- References -- House Price Prediction via Visual Cues and Estate Attributes -- 1 Introduction -- 2 Related Work -- 3 Proposed Work -- 3.1 Data Collection -- 3.2 Computational Model -- 4 Experiments -- 4.1 Evaluation Metrics -- 4.2 Experimental Results -- 4.3 Ablation Studies -- 5 Conclusion and Future Works -- References -- DRB-Net: Dilated Residual Block Network for Infrared Image Restoration -- 1 Introduction -- 2 Related Work.
2.1 Non-learning Denoising Methods -- 2.2 Discriminative Learning Denoising Methods -- 2.3 Deep Learning for IR Imaging -- 3 Proposed Architecture -- 3.1 Why Dilated Convolution? -- 3.2 Residual Blocks -- 3.3 Architecture and Compared Methods -- 4 Dataset -- 4.1 Sample Preparation and Image Acquisition -- 4.2 Dataset Creation -- 4.3 Implementation -- 5 Experiments -- 5.1 DRB-Net Specification -- 5.2 Denoising of Synthetic Noisy Data -- 5.3 Generalization and Robustness Test -- 6 Conclusion and Future Work -- References -- Segmentation and Tracking -- Saliency Can Be All You Need in Contrastive Self-supervised Learning -- 1 Introduction -- 2 Motivation and Background -- 2.1 Related Work -- 2.2 Concrete Background -- 3 Implementation, Setup and Results -- 3.1 Setup and Datasets -- 3.2 Preliminary: Running SGD on NORCE-PV and MultiRes-PV Datasets -- 3.3 An Efficient Implementation -- 3.4 Using SGD as an Augmentation Policy in Contrastive SSL Algorithms -- 4 Discussion -- 5 Conclusions -- References -- GCEENet: A Global Context Enhancement and Exploitation for Medical Image Segmentation -- 1 Introduction -- 2 Related Work -- 2.1 Convolutional Neural Networks for Semantic Segmentation -- 2.2 Contextual Information Modeling -- 3 Proposed Architecture -- 3.1 Overview -- 3.2 Global Context Encoder Module -- 3.3 Local Distribution -- 3.4 Aggregator Module -- 3.5 Loss Function -- 4 Experiments and Discussion -- 4.1 Benchmark Datasets -- 4.2 Experiment Settings -- 5 Results and Discussion -- 5.1 Ablation Study -- 5.2 Comparison to Baseline Models -- 6 Conclusion -- References -- V2F: Real Time Video Segmentation with Apache Flink -- 1 Introduction -- 2 Related Work -- 3 Video2Flink Architecture -- 3.1 V2F Operators -- 4 Experiments -- 5 Conclusions and Future Work -- References -- Joint Discriminative and Metric Embedding Learning for Person Re-identification.
1 Introduction -- 2 Related Work -- 3 Proposed Approach -- 3.1 Classification Losses -- 3.2 Metric Learning Loss -- 3.3 Joint Classification and Metric Loss -- 3.4 Network Architecture -- 4 Experiments -- 4.1 Implementation Details -- 4.2 Comparison with State-of-the-Art Methods -- 4.3 Ablation Study -- 5 Conclusions -- References -- Transformer Networks for Future Person Localization in First-Person Videos -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Problem Overview -- 3.2 Input Overview -- 3.3 Implementation Details -- 4 Experiments -- 4.1 Evaluation Metrics and Baselines -- 4.2 Quantitative Results -- 4.3 Additional Analysis -- 4.4 Inference Time Analysis -- 5 Conclusion -- References -- Virtual Reality -- VR-SFT: Reproducing Swinging Flashlight Test in Virtual Reality to Detect Relative Afferent Pupillary Defect -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Swinging Flashlight Test in Virtual Reality -- 3.2 VR Implementation and Experimental Software -- 3.3 RAPD Scoring -- 4 Dataset -- 5 Data Analysis and Results -- 6 Discussion and Future Work -- References -- A Quantitative Analysis of Redirected Walking in Virtual Reality Using Saccadic Eye Movements -- 1 Introduction -- 2 Methodology -- 2.1 Simulation and Hardware -- 2.2 Simulation Tasks and Data Collection -- 2.3 Eye Tracking -- 2.4 Questionnaire -- 2.5 Demographics -- 3 Results -- 4 Conclusion and Future Work -- References -- A DirectX-Based DICOM Viewer for Multi-user Surgical Planning in Augmented Reality -- 1 Introduction -- 2 Related Work -- 2.1 Holographic DICOM Viewer Prototypes -- 2.2 Interaction with 3D Objects -- 3 System Design Overview -- 4 Direct3D-Based DICOM Viewer Implementation -- 4.1 Smartphones as User Input Devices -- 4.2 Functionalities -- 4.3 Marker-Based 3D Object Placement -- 5 User Interactions -- 5.1 Virtual 2D Plane Touch.
5.2 3D User Interaction -- 6 Experiments -- 7 Conclusions -- References -- Virtual-Reality Based Vestibular Ocular Motor Screening for Concussion Detection Using Machine-Learning -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Naive Bayes -- 3.2 Decision Tree -- 3.3 Random Forest -- 3.4 Support Vector Classifer -- 3.5 AdaBoost -- 3.6 Gaussian Process Classifier -- 3.7 Logistic Regression -- 3.8 Perceptron -- 3.9 Isolation Forest -- 3.10 One Class SVM -- 4 Experimental Analysis -- 4.1 Data Collection Using Virtual-Reality Headset -- 4.2 Data Splitting for Training and Testing -- 4.3 Qualitative Evaluation -- 4.4 Quantitative Evaluation -- 5 Conclusion -- References -- Posters -- GUILD - A Generator for Usable Images in Large-Scale Datasets -- 1 Introduction -- 2 Related Work -- 2.1 Manual Collection of Datasets -- 2.2 Synthetic Generation of Datasets -- 3 Implementation -- 3.1 Approach -- 3.2 Object Models -- 3.3 Environments -- 3.4 Label Generation -- 4 Evaluation -- 4.1 Evaluation Design -- 4.2 Evaluation Datasets -- 4.3 Accuracy -- 4.4 Generalizability -- 4.5 Variety -- 5 Conclusion and Future Work -- References -- Distributional Semantics of Line Charts for Trend Classification -- 1 Introduction -- 2 Dataset -- 3 Related Work -- 3.1 Information Graphic Description Generation -- 3.2 Prototype Learning -- 3.3 Bag of Words for Computer Vision -- 3.4 Distributional Semantics -- 4 Architecture and Methodology -- 4.1 Forming the Vocabulary -- 4.2 Line Chart Embeddings -- 4.3 Classification -- 5 Implementation -- 6 Experiments and Results -- 6.1 Classification Task -- 6.2 Results -- 7 Discussion -- 8 Conclusion -- References -- Deep Learning Hyperparameter Optimization for Breast Mass Detection in Mammograms -- 1 Introduction -- 2 Background and Motivation -- 2.1 End-to-End Pipeline -- 2.2 Genetic Algorithm -- 2.3 Binary Tournament Selection.
2.4 Simulated Binary Crossover (SBX).
Record Nr. UNINA-9910634045803321
Cham, Switzerland : , : Springer, , [2022]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Advances in visual computing : 17th international symposium, ISVC 2022, San Diego, CA, USA, October 3-5, 2022, proceedings, part I / / edited by George Bebis [and eight others]
Advances in visual computing : 17th international symposium, ISVC 2022, San Diego, CA, USA, October 3-5, 2022, proceedings, part I / / edited by George Bebis [and eight others]
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2022]
Descrizione fisica 1 online resource (486 pages)
Disciplina 929.605
Collana Lecture Notes in Computer Science
Soggetto topico Computers
ISBN 3-031-20713-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Keynote Talks -- Towards Scaling Up GANs -- Sensible Machine Learning for Geometry -- Designing Augmented Reality for the Future of Work -- The Future of Visual Computing via Foundation Models (Banquet Keynote Talk) -- 3D Reconstruction: Leveraging Synthetic Data for Lightweight Reconstruction -- Human-AI Interaction in Visual Analytics: Designing for the "Two Black Boxes" Problem -- Contents - Part I -- Contents - Part II -- Deep Learning I -- Unsupervised Structure-Consistent Image-to-Image Translation -- 1 Introduction -- 2 Background and Related Work -- 3 Method -- 3.1 Encoder -- 3.2 Generator -- 3.3 Structure and Texture Disentanglement -- 3.4 Objective Function -- 4 Experiments -- 4.1 Comparison to State-of-the-Art -- 5 Applications -- 5.1 Addressing Bias in Training Datasets -- 5.2 Training Datasets for Semantic Segmentation of Satellite Images -- 6 Discussion and Limitations -- 7 Conclusions -- References -- Learning Representations for Masked Facial Recovery -- 1 Introduction -- 2 Relevant Works -- 3 Method -- 3.1 Baseline Model -- 3.2 Unmasking Model -- 3.3 Datasets -- 3.4 Implementation Details -- 4 Experimental Results -- 5 Conclusions -- References -- Deep Learning Based Shrimp Classification -- 1 Introduction -- 2 Related Work -- 3 Proposed Approach -- 3.1 Acquisition -- 3.2 Preprocessing -- 3.3 Classification -- 4 Experimental Results -- 5 Conclusions -- References -- Gait Emotion Recognition Using a Bi-modal Deep Neural Network -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 4 Experimental Results -- 5 Conclusion and Future Work -- References -- Attacking Frequency Information with Enhanced Adversarial Networks to Generate Adversarial Samples -- 1 Introduction -- 2 Related Work -- 2.1 Adversarial Samples -- 2.2 Black-Box Attacks -- 2.3 Frequency Features and Attacks.
3 Our Frequency Attack Approach -- 3.1 Separate High and Low Frequency Information -- 3.2 Dual Discriminators Support Attack -- 3.3 Frequency Attack Framework -- 3.4 Network Architecture -- 3.5 Loss Function -- 4 Experiments -- 4.1 Evaluation Metric -- 4.2 Ablation Study -- 4.3 Transferability of FAF -- 4.4 Attack Under Defenses -- 5 Conclusion -- References -- Visualization -- Explainable Interactive Projections for Image Data -- 1 Introduction -- 2 Related Work -- 2.1 Interactive Dimensionality Reduction -- 2.2 Semantic Interaction -- 2.3 Explainability in Deep Learning -- 3 Tasks -- 3.1 Define Custom Similarities Based on Prior Knowledge -- 3.2 Link Human and Machine Defined Similarities -- 4 Workflow and Methodology -- 4.1 Initial State -- 4.2 Interactions and Inverse Projection -- 4.3 Visual Explanations -- 5 Usage Scenario: Edamame Pods -- 6 Discussion -- 7 Conclusion -- References -- MultiProjector: Temporal Projection for Multivariates Time Series -- 1 Introduction -- 2 Related Work -- 2.1 Visualizing High Dimensional Temporal Datasets -- 2.2 Dimension Reduction -- 3 Methodology -- 3.1 Clusterings -- 3.2 Multidimensional Projections -- 3.3 Visualizing the Time Dimension -- 3.4 Multivariate Representations -- 4 Use Cases -- 4.1 Use Case 1: Monthly US Employment Rate -- 4.2 Use Case 2: Monitoring Computer Metrics -- 4.3 Use Case 3: Plant Genetics -- 4.4 Discussion -- 5 Conclusion -- References -- Deep Learning Based Super-Resolution for Medical Volume Visualization with Direct Volume Rendering -- 1 Introduction -- 2 Related Work -- 2.1 Image and Video Super-resolution -- 2.2 Resolution Enhancement for Rendered Content -- 3 Methodology -- 3.1 Direct Volume Rendering Framework -- 3.2 Network Architecture -- 4 Dataset -- 5 Evaluation -- 5.1 Performance Gain with Additional Feature at the Input.
5.2 Performance Gain with Additional Previous Frames -- 5.3 Upsampling Ratio -- 6 Conclusion and Future Work -- References -- Interactive Virtual Reality Exploration of Large-Scale Datasets Using Omnidirectional Stereo Images -- 1 Introduction -- 2 Related Work -- 2.1 Image-Based Visualization -- 2.2 Virtual Reality for Large-Scale Data Sets -- 3 Science Drivers -- 3.1 Cancer Cell Transport -- 3.2 Graphene Superlubricity -- 4 Cinema ODS Image Database -- 4.1 Rendering -- 5 Interactive Cinema ODS Viewer -- 6 Evaluation -- 6.1 Visualization Latency -- 6.2 VR Frame Rate -- 6.3 Qualitative Feedback -- 7 Conclusion -- References -- A Quantitative Analysis of Labeling Issues in the CelebA Dataset -- 1 Introduction -- 2 Related Work -- 3 Incorrect Labels -- 3.1 Contradicting and Conflicting Labels -- 3.2 Mislabeling -- 4 Inconsistent Labels -- 4.1 Consistency -- 4.2 Agreement -- 4.3 Correlated Labels -- 5 Conclusion -- References -- Object Detection and Recognition -- Recognition of Aquatic Invasive Species Larvae Using Autoencoder-Based Feature Averaging -- 1 Introduction -- 2 Related Work -- 2.1 Aquatic Invasive Species -- 2.2 Local Responses to Aquatic Invasive Species -- 2.3 Classification with Image Sets -- 2.4 Underwater Image Classification -- 2.5 Autoencoders -- 3 Methodology -- 3.1 Solution Description -- 3.2 Convolutional Autoencoder -- 3.3 Classification Model -- 3.4 Activation Functions -- 3.5 Loss Functions -- 3.6 Base Model -- 3.7 Dataset -- 4 Results -- 4.1 Evaluation Metric -- 4.2 Quantitative Analysis -- 4.3 Comparative Analysis -- 5 Conclusion -- References -- Subspace Analysis for Multi-temporal Disaster Mapping Using Satellite Imagery -- 1 Introduction -- 2 Subspace Learning-Based Disaster Mapping -- 2.1 Region Delineation -- 2.2 Segmentation Fusion -- 2.3 Subspace Learning for Disaster Mapping.
3 Determining the Changed and Unchanged Regions -- 4 Experiments, Results and Discussion -- 4.1 Experimental Setup -- 4.2 Results and Discussion -- 5 Conclusion -- References -- Open-Set Plankton Recognition Using Similarity Learning -- 1 Introduction -- 2 Related Work -- 2.1 Plankton Recognition -- 2.2 Open-Set Classification -- 2.3 Classification by Metric Learning -- 3 Proposed Method -- 3.1 Angular Margin Loss -- 4 Experiments -- 4.1 Data -- 4.2 Description of Experiments -- 4.3 Results -- 5 Conclusions -- References -- Sensor Fusion Operators for Multimodal 2D Object Detection -- 1 Introduction -- 2 Related Work -- 3 Camera-LiDAR 2D Object Detector -- 4 Sensor Fusion Operators -- 5 Experimental Results -- 5.1 Experimental Setting -- 5.2 Evaluation of Early Sensor Fusion -- 5.3 Evaluation of Mid-Level Sensor Fusion -- 5.4 Complexity Analysis -- 6 Conclusion -- References -- Learning When to Say ``I Don't Know -- 1 Introduction -- 2 Preliminaries -- 3 Related Work -- 4 Proposed Method -- 5 Experiments -- 5.1 Synthetic Data -- 5.2 Image Datasets -- 5.3 Text Datasets -- 5.4 Generalization from Validation to Test Data -- 5.5 Alternative Confidence Interval Formulations -- 5.6 Discussion -- 6 Conclusion -- References -- Multi-class Detection and Tracking of Intracorporeal Suturing Instruments in an FLS Laparoscopic Box Trainer Using Scaled-YOLOv4 -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Scaled-YOLOv4 Architecture -- 3.2 Measurement Algorithm -- 4 Experimental Setup -- 4.1 Dataset -- 4.2 Software Implementation -- 5 Results -- 6 Discussion -- 7 Conclusion and Future Work -- References -- Deep Learning II -- A New Approach to Visual Classification Using Concatenated Deep Learning for Multimode Fusion of EEG and Image Data -- 1 Introduction -- 2 Related Work -- 3 Datasets -- 3.1 EEG-ImageNet.
3.2 Visual Stimuli EEG Dataset: Real-World 3D Objects and Corresponding 2D Image Stimuli -- 4 Data Encoding and Processing -- 4.1 Classical Feature Extraction for EEG Data -- 4.2 Classical Feature Extraction for Image Data -- 4.3 Principal Component Analysis (PCA) Encoding -- 4.4 Grayscale-Image Encoding for EEG Data -- 5 Methods and Model Implementation -- 5.1 Conventional Machine Learning Classifiers -- 5.2 LSTM-Based EEG Model (LEM) ch17ourvisclasspaper -- 5.3 CNN-Based Image Model (CIM) ch17ourvisclasspaper -- 5.4 Grayscale-Image Encoded EEG Model (GEM) -- 5.5 Concatenation-Based Models ch17ourvisclasspaper -- 6 Experiments and Results -- 6.1 Baseline Visual Classification for EEG and Image Data -- 6.2 Classification Using Deep Learning Models -- 6.3 Hemispherical Brain Region Classification Comparison -- 6.4 Visual Classification Using Multimodal Deep Learning -- 6.5 Visual Classification for Real Object Versus Image as Stimuli -- 7 Discussion -- 8 Conclusion -- References -- Deep Learning-Based Classification of Plant Xylem Tissue from Light Micrographs -- 1 Introduction -- 2 Related Works -- 3 Dataset and Problem Definition -- 4 Methodology -- 4.1 Data Augmentation and Pre-processing -- 4.2 Cascading-Like Model -- 4.3 Global Contextualization Approach -- 5 Experiments and Results -- 5.1 Model Evaluation Metric -- 5.2 Baseline Results -- 5.3 Results -- 6 Discussion -- 7 Conclusion -- References -- VampNet: Unsupervised Vampirizing of Convolutional Networks -- 1 Introduction -- 2 Related Work -- 2.1 Correlation-Based Feature Map Analysis -- 2.2 Multitask Neural Networks -- 2.3 Networks Merging -- 3 Method -- 3.1 Linearity Between Feature Maps -- 3.2 Ranking Linearity Between Features -- 3.3 Vampirizing a Feature Using a Convolutional Operator -- 3.4 Vampirizing a Layer -- 3.5 Automatic Selection of the Layer to Be Replaced -- 4 Experiments.
4.1 Setup.
Record Nr. UNISA-996503470603316
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Advances in visual computing . Part I : 16th International Symposium, ISVC 2021, Virtual event, October 4-6, 2021, Proceedings / / George Bebis [and eight others], editors
Advances in visual computing . Part I : 16th International Symposium, ISVC 2021, Virtual event, October 4-6, 2021, Proceedings / / George Bebis [and eight others], editors
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (635 pages)
Disciplina 006.6
Collana Lecture Notes in Computer Science
Soggetto topico Computer graphics
ISBN 3-030-90439-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910512174103321
Cham, Switzerland : , : Springer, , [2021]
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Advances in visual computing . Part 2 : 16th International Symposium, ISVC 2021, Virtual event, October 4-6, 2021, Proceedings / / George Bebis [and eight others], editors
Advances in visual computing . Part 2 : 16th International Symposium, ISVC 2021, Virtual event, October 4-6, 2021, Proceedings / / George Bebis [and eight others], editors
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (555 pages)
Disciplina 006.6
Collana Lecture Notes in Computer Science
Soggetto topico Computer graphics
ISBN 3-030-90436-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910512174203321
Cham, Switzerland : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Advances in visual computing . Part I : 16th International Symposium, ISVC 2021, Virtual event, October 4-6, 2021, Proceedings / / George Bebis [and eight others], editors
Advances in visual computing . Part I : 16th International Symposium, ISVC 2021, Virtual event, October 4-6, 2021, Proceedings / / George Bebis [and eight others], editors
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (635 pages)
Disciplina 006.6
Collana Lecture Notes in Computer Science
Soggetto topico Computer graphics
ISBN 3-030-90439-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNISA-996464448703316
Cham, Switzerland : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
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Advances in visual computing . Part 2 : 16th International Symposium, ISVC 2021, Virtual event, October 4-6, 2021, Proceedings / / George Bebis [and eight others], editors
Advances in visual computing . Part 2 : 16th International Symposium, ISVC 2021, Virtual event, October 4-6, 2021, Proceedings / / George Bebis [and eight others], editors
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (555 pages)
Disciplina 006.6
Collana Lecture Notes in Computer Science
Soggetto topico Computer graphics
ISBN 3-030-90436-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNISA-996464446803316
Cham, Switzerland : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
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Advances in visual computing : 15th international symposium, ISVC 2020, San Diego, CA, USA, October 5-7, 2020, proceedings, part II / / George Bebis [and eight others]
Advances in visual computing : 15th international symposium, ISVC 2020, San Diego, CA, USA, October 5-7, 2020, proceedings, part II / / George Bebis [and eight others]
Edizione [1st ed. 2020.]
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2020]
Descrizione fisica 1 online resource (XXVIII, 777 p. 351 illus., 296 illus. in color.)
Disciplina 006.4
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico Artificial intelligence
Image Processing and Computer Vision
Pattern perception
ISBN 3-030-64559-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Object Recognition/Detection/Categorization -- Few-shot Image Recognition with Manifolds -- A scale-aware YOLO model for pedestrian detection -- Image categorization using Agglomerative clustering based smoothed Dirichlet mixtures -- SAT-CNN: A Small Neural Network for Object Recognition from Satellite Imagery -- Domain Adaptive Transfer Learning on Visual Attention Aware Data Augmentation for Fine-grained Visual Categorization -- 3D Reconstruction -- A Light-Weight Monocular Depth Estimation With Edge-Guided Occlusion Fading Reduction -- Iterative Closest Point with Minimal Free Space Constraints -- Minimal Free Space Constraints for Implicit Distance Bounds -- Medical Image Analysis -- Fetal Brain Segmentation using Convolutional Neural Networks with Fusion Strategies -- Fundus2Angio: A Novel Conditional GAN Architecture for Generating Fluorescein Angiography Images from Retinal Fundus Photography -- Multiscale Detection of Cancerous Tissue in High Resolution Slide Scans -- DeepTKAClassi er: Brand Classification of Total Knee Arthroplasty Implants using Explainable Deep Convolutional Neural Networks -- Multi-modal Image Fusion based on Weight Local Features and Novel Sum-Modified-Laplacian in Non-Subsampled Shearlet Transform Domain -- Robust Prostate Cancer Classification with Siamese Neural Networks -- Vision for Robotics -- Simple Camera-to-2D-LiDAR Calibration Method for General Use -- SalsaNext: Fast, Uncertainty-aware Semantic Segmentation of LiDAR Point Clouds -- Mobile Manipulator Robot Visual Servoing and Guidance for Dynamic Target Grasping -- Statistical Pattern Recognition -- Interpreting Galaxy Deblender GAN from the Discriminator's Perspective -- Variational Bayesian Sequence to Sequence Networks for Memory-Efficient Sign Language Translation -- A Gaussian Process Upsampling Model for Improvements in Optical Character Recognition -- Posters -- Video based fire detection using Xception and ConvLSTM -- Highway Traffic Classification for the Perception Level of Situation Awareness -- 3D-CNN for Facial Emotion Recognition in Videos -- Reducing Triangle Inequality Violations with Deep Learning and Its Application to Image Retrieval -- A Driver Guidance System to Support the Stationary Wireless Charging of Electric Vehicles -- An Efficient Tiny Feature Map Network For Real-Time Semantic Segmentation -- A Modified Syn2Real Network for Nighttime Rainy Image Restoration -- Unsupervised domain adaptation for person re-identification with few and unlabeled target data -- How Does Computer Animation Affect Our Perception Of Emotions in Video Summarization? -- Where's Wally: A Gigapixel Image Study for Face Recognition in Crowds -- Optical Flow Based Background Subtraction with a Moving Camera: Application to Autonomous Driving -- Deep Facial Expression Recognition with Occlusion Regularization -- Semantic Segmentation with Peripheral Vision -- Generator From Edges: Reconstruction of Facial Images -- CD2 : Combined Distances of Contrast Distributions for Image Quality Analysis -- Real-Time Person Tracking and Association on Doorbell Cameras -- MySnapFoodLog: Culturally Sensitive FoodPhoto-Logging App for Dietary BiculturalismStudies -- Hand Gesture Recognition Based on the Fusion of Visual and Touch Sensing Data -- Gastrointestinal Tract Anomaly Detection from Endoscopic Videos using Object Detection Approach -- A multimodal high level video segmentation for content targeted online advertising -- AI Playground: Unreal Engine-based Data Ablation Tool for Deep Learning -- Homework Helper: Providing Valuable Feedback on Math Mistakes -- Interface Design for HCI Classroom: From Learners' Perspective -- Pre-trained Convolutional Neural Network for the Diagnosis of Tuberculosis -- Near-Optimal Concentric Circles Layout -- Facial Expression Recognition and Ordinal Intensity Estimation: A Multilabel Learning Approach -- Prostate MRI Registration Using Siamese Metric Learning -- Unsupervised Anomaly Detection of the First Person in Gait from an Egocentric Camera -- Emotion Categorization from Video-frame Images using a Novel Sequential Voting Technique -- Systematic Optimization of Image Processing Pipelines Using GPUs -- A Hybrid Approach for Improved Image Similarity Using Semantic Segmentation -- Automated classification of Parkinson's Disease using Diffusion Tensor Imaging Data -- Nonlocal Adaptive Biharmonic Regularizer for Image Restoration -- A Robust Approach to Plagiarism Detection in Handwritten Documents -- Optical Coherence Tomography Latent Fingerprint Image Denoising -- CNN, Segmentation or Semantic Embeddings: Evaluating Scene Context for Trajectory Prediction -- Automatic Extraction of Joint Orientations in Rock Mass using PointNet and DBSCAN -- Feature Map Retargeting to Classify Biomedical Journal Figures -- Automatic 3D Object Detection from RGB-D data using PU-GAN -- Nodule Generation of Lung CT Images using a 3D Convolutional LSTM Network -- Conditional GAN for Prediction of Glaucoma Progression with Macular Optical Coherence Tomography.
Record Nr. UNINA-9910447250403321
Cham, Switzerland : , : Springer, , [2020]
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Advances in visual computing : 15th international symposium, ISVC 2020, San Diego, CA, USA, October 5-7, 2020, proceedings, part I / / George Bebis [and eight others]
Advances in visual computing : 15th international symposium, ISVC 2020, San Diego, CA, USA, October 5-7, 2020, proceedings, part I / / George Bebis [and eight others]
Edizione [1st ed. 2020.]
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2020]
Descrizione fisica 1 online resource (XXXVI, 745 p. 45 illus., 1 illus. in color.)
Disciplina 006.4
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico Image Processing and Computer Vision
Artificial intelligence
Pattern perception
ISBN 3-030-64556-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Deep Learning -- Regularization and Sparsity for Adversarial Robustness and Stable Attribution -- Self-Competitive Neural Networks -- A Novel Contractive GAN Model for a Unified Approach Towards Blind Quality Assessment of Images from Heterogeneous Sources -- Nonconvex Regularization for Network Slimming: Compressing CNNs Even More -- Biologically Inspired Sleep Algorithm for VariationalAuto-Encoders -- A Deep Genetic Programming based Methodology for Art Media Classification Robust to Adversarial Perturbations -- rcGAN: Learning a generative model for arbitrary size image generation -- Sketch-Inspector: a Deep Mixture Model for High-Quality Sketch Generation of Cats -- Depthwise Separable Convolutions and Variational Dropout within the context of YOLOv3 -- Uncertainty Estimates in Deep Generative Models using Gaussian Processes -- Segmentation -- Towards Optimal Ship Navigation Using Image Processing -- Overscan Detection in Digitized Analog Films by Precise Sprocket Hole Segmentation -- Pixel-level Corrosion Detection on Metal Constructions by Fusion of Deep Learning Semantic and Contour Segmentation -- CSC-GAN: Cycle and semantic consistency for dataset augmentation -- Improvements on the Superpixel Hierarchy Algorithm with Applications to Image Segmentation and Saliency Detection -- Visualization -- Referenced Based Color Transfer for Medical Volume Rendering -- An Empirical Methodological Study of Evaluation Methods Applied to Educational Timetabling Visualizations -- Real-Time Contrast Enhancement for 3DMedical Images using Histogram Equalization -- Flow Map Processing by Space-Time Deformation -- GenExplorer: Visualizing and Comparing Gene Expression Levels via Differential Charts -- Video Analysis and Event Recognition -- An Event-Based Hierarchical Method for Customer Activity Recognition in Retail Stores -- Fully Autonomous UAV-based Action Recognition System Using Aerial Imagery -- Hierarchical Action Classification with Network Pruning -- An Approach Towards Action Recognition using Part Based Hierarchical Fusion -- ST: Computational Bioimaging -- Ensemble Convolutional Neural Networks for the Detection of Microscopic Fusarium Oxysporum -- Offline versus Online Triplet Mining based on Extreme Distances of Histopathology Patches -- Multi-Label Classification of Panoramic Radiographic Images using a Convolutional Neural Network -- Ink Marker Segmentation in Histopathology Images Using Deep Learning -- P-FideNet: Plasmodium Falciparum Identification Neural Network -- Applications -- Lightless Fields: Enhancement and Denoising of Light-defficient Light Fields -- FA3D: Fast and Accurate 3D Object Detection -- Generalized Inverted Dirichlet Optimal predictor for Image inpainting -- BVNet: A 3D End-to-end Model Based on Point Cloud -- Evaluating Single Image Dehazing Methods Under Realistic Sunlight Haze -- Biometrics -- Deep Partial Occlusion Facial Expression Recognition via Improved CNN -- Towards an Effective Approach for Face Recognition with DCGANs Data Augmentation -- Controlled AutoEncoders to Generate Faces from Voices -- Gender and Age Estimation without Facial Information from Still Images -- Face Reenactment Based Facial Expression Recognition -- Motion and Tracking -- Coarse-to-Fine Object Tracking Using Deep Features and Correlation Filters -- Asynchronous Corner Tracking Algorithm based on Lifetime of Events for DAVIS Cameras -- TAGCN: Topology-Aware Graph Convolutional Network for Trajectory Prediction -- 3D articulated body model using anthropometric control points and an articulation video -- Body Motion Analysis for Golf Swing Evaluation -- Computer Graphics -- Simulation of High-Definition Pixel-Headlights -- ConcurrentHull: A Fast Parallel Computing Approach to the Convex Hull Problem -- A Data-Driven Creativity Measure for 3D Shapes -- Virtual Reality -- Walking in a Crowd Full of Virtual Characters: Effects of Virtual Character Appearance on Human Movement Behavior -- Improving Chinese Reading Comprehensions of Dyslexic Children via VR Reading -- Improving User Experience in Augmented Reality Mirrors with 3D Displays -- Passenger Anxiety about Virtual Driver Awareness During a Trip with a Virtual Autonomous Vehicle -- Investigating the Display Fidelity of Popular Head-Mounted Display Systems on Spatial Updating and Learning in VR -- ST: Computer Vision Advances in Geo-Spatial Applications and Remote Sensing -- Natural Disaster Building Damage Assessment Using a Two-Encoder U-Net -- Understanding Flooding Detection Using Overhead Imagery – Lessons Learned -- Hyperspectral Image Classification via Pyramid Graph Reasoning -- Semi-Supervised Fine-Tuning for Deep Learning Models in Remote Sensing Applications -- Scene Classification of Remote Sensing Images using convNet Features and Multi-grained Forest.
Record Nr. UNINA-9910447250503321
Cham, Switzerland : , : Springer, , [2020]
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