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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 | ||
| ||
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 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Advances in Visual Computing : 17th International Symposium, ISVC 2022, San Diego, CA, USA, October 3–5, 2022, Proceedings, Part I / / edited by George Bebis, Bo Li, Angela Yao, Yang Liu, Ye Duan, Manfred Lau, Rajiv Khadka, Ana Crisan, Remco Chang
| Advances in Visual Computing : 17th International Symposium, ISVC 2022, San Diego, CA, USA, October 3–5, 2022, Proceedings, Part I / / edited by George Bebis, Bo Li, Angela Yao, Yang Liu, Ye Duan, Manfred Lau, Rajiv Khadka, Ana Crisan, Remco Chang |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
| Descrizione fisica | 1 online resource (486 pages) |
| Disciplina |
929.605
006.37 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Image processing - Digital techniques
Computer vision Artificial intelligence Computer engineering Computer networks Social sciences - Data processing Computer Imaging, Vision, Pattern Recognition and Graphics Artificial Intelligence Computer Engineering and Networks Computer Application in Social and Behavioral Sciences |
| ISBN |
9783031207136
3031207130 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Deep Learning I -- Visualization -- Object Detection and Recognition -- Deep Learning II -- Video Analysis and Event Recognition -- Computer Graphics -- ST: Biomedical Imaging Techniques for Cancer Detection, Diagnosis and Management. |
| Record Nr. | UNINA-9910634049103321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in Visual Computing : 17th International Symposium, ISVC 2022, San Diego, CA, USA, October 3–5, 2022, Proceedings, Part II / / edited by George Bebis, Bo Li, Angela Yao, Yang Liu, Ye Duan, Manfred Lau, Rajiv Khadka, Ana Crisan, Remco Chang
| Advances in Visual Computing : 17th International Symposium, ISVC 2022, San Diego, CA, USA, October 3–5, 2022, Proceedings, Part II / / edited by George Bebis, Bo Li, Angela Yao, Yang Liu, Ye Duan, Manfred Lau, Rajiv Khadka, Ana Crisan, Remco Chang |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2022 |
| Descrizione fisica | 1 online resource (466 pages) |
| Disciplina |
929.605
005.118 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Image processing - Digital techniques
Computer vision Computer engineering Computer networks Artificial intelligence Education - Data processing Social sciences - Data processing Computer Imaging, Vision, Pattern Recognition and Graphics Computer Engineering and Networks Artificial Intelligence Computers and Education Computer Application in Social and Behavioral Sciences |
| ISBN |
9783031207167
3031207165 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | ST: Neuro-inspired Artificial Intelligence -- Applications -- Segmentation and Tracking -- Virtual Reality -- Poster. |
| Record Nr. | UNINA-9910634045803321 |
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
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 | ||
| ||
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 | ||
| ||
Advances in Visual Computing : 16th International Symposium, ISVC 2021, Virtual Event, October 4-6, 2021, Proceedings, Part I / / edited by George Bebis, Vassilis Athitsos, Tong Yan, Manfred Lau, Frederick Li, Conglei Shi, Xiaoru Yuan, Christos Mousas, Gerd Bruder
| Advances in Visual Computing : 16th International Symposium, ISVC 2021, Virtual Event, October 4-6, 2021, Proceedings, Part I / / edited by George Bebis, Vassilis Athitsos, Tong Yan, Manfred Lau, Frederick Li, Conglei Shi, Xiaoru Yuan, Christos Mousas, Gerd Bruder |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 |
| Descrizione fisica | 1 online resource (635 pages) |
| Disciplina | 006.6 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Pattern recognition systems
Computer vision Artificial intelligence Computer engineering Computer networks Automated Pattern Recognition Computer Vision Artificial Intelligence Computer Engineering and Networks |
| ISBN | 3-030-90439-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Keynote Talks -- Embodied Perception in-the-Wild -- Design Tools for Material Appearance -- Guidance-Enriched Visual Analytics: Challenges and Opportunities -- Learning and Accruing Knowledge over Time Using Modular Architectures -- Combining Brain-Computer Interfaces and Virtual Reality: Novel 3D Interactions and Promising Applications -- Direct Estimation of Appearance Models for Image Segmentation -- Contents - Part I -- Contents - Part II -- Deep Learning I -- Real-World Thermal Image Super-Resolution -- 1 Introduction -- 2 Related Work -- 2.1 RGB Image Super-Resolution -- 2.2 Thermal Image Super-Resolution -- 3 Dataset -- 4 Thermal RealSR -- 4.1 Realistic Degradation Using KernelGAN and Noise Injection -- 4.2 Super-Resolution Model -- 5 Experiments and Results -- 5.1 Evaluation Metrics -- 5.2 Comparison with the State of the Art -- 6 Conclusion -- References -- QR Code Style Transfer Method Based on Conditional Instance Regularization -- 1 Introduction -- 2 Related Works -- 2.1 QR Code Style Transfer System -- 2.2 Structure of the Style Transfer Network -- 3 Style Transfer Network Based on Conditional Instance Regularization -- 3.1 Conditional Instance Regularization -- 3.2 Residual Connected Module -- 3.3 Style Transfer Network Structure -- 3.4 Weighted Fusion Correction for Styled QR Codes -- 3.5 Artistic Style QR Code Dynamics -- 4 Experiment -- 4.1 Training -- 4.2 Single-Style Training -- 4.3 Multi-style Training -- 4.4 Comparison of Experiment Results -- 5 Conclusion -- References -- Multimodal Multi-tasking for Skin Lesion Classification Using Deep Neural Networks -- 1 Introduction -- 2 Methodology -- 2.1 Dataset -- 2.2 ABCD Rule Feature Extraction -- 2.3 Proposed Model -- 2.4 Class Balancing Techniques -- 3 Experiments -- 3.1 ABCD Rule for Multimodal Multi-tasking.
3.2 Role of Segmentation in Lesion Classification -- 4 Results and Discussion -- 5 Conclusion -- References -- DeepSolfège: Recognizing Solfège Hand Signs Using Convolutional Neural Networks -- 1 Introduction -- 2 Related Work -- 3 Dataset -- 3.1 Labels -- 3.2 Preprocessing -- 4 Method -- 4.1 CNN Architecture -- 4.2 Training -- 4.3 Ablation Study -- 5 Evaluation -- 5.1 Real World Application -- 6 Conclusion -- References -- Image Prior Transfer and Ensemble Architectures for Parkinson's Disease Detection -- 1 Introduction -- 2 Background and Related Works -- 3 Proposed Method -- 3.1 Dataset -- 3.2 Preprocessing -- 3.3 Models -- 3.4 Ensemble Architecture 1 -- 3.5 Ensemble Architecture 2 -- 4 Experimental Results -- 5 Occlusion Analysis to Locate Relevant Regions -- 5.1 Occlusion Analysis for Modified ResNet -- 5.2 Occlusion Analysis for Ensemble Architecture - Model 1 -- 6 Conclusion and Future Works -- References -- Computer Graphics I -- BRDF Measurement of Real Materials Using Handheld Cameras -- 1 Introduction -- 2 BRDF Measurement Using Handheld Cameras -- 2.1 Use of Bivariate BRDF -- 2.2 BRDF Sampling -- 2.3 Dense BRDF Estimation -- 3 BRDF Measurement of Real Materials -- 3.1 Experimental Setup -- 3.2 Estimation Results -- 3.3 Measurement Time -- 4 Conclusion -- References -- SORGATE: Extracting Geometry and Texture from Images of Solids of Revolution -- 1 Introduction -- 2 Previous Work -- 3 Design -- 4 Implementation -- 5 Evaluation -- 6 Conclusions and Future Work -- References -- Putting Table Cartograms into Practice -- 1 Introduction -- 2 Related Work -- 3 TCarto: An Optimization Based Algorithm -- 4 Potential Applications -- 5 Experimental Results -- 6 Limitations and Directions for Future Research -- References -- Perceived Naturalness of Interpolation Methods for Character Upper Body Animation -- 1 Introduction -- 2 Prior Work. 3 Methods -- 3.1 Studied Interpolations -- 3.2 Study Design -- 3.3 Experiment Design -- 3.4 Study Procedure -- 3.5 Data Collection and Analysis -- 4 Discussion -- 5 Conclusion and Future Work -- References -- Neuromuscular Control of the Face-Head-Neck Biomechanical Complex with Learning-Based Expression Transfer from Images and Videos -- 1 Introduction -- 2 Related Work -- 3 Musculoskeletal Model -- 3.1 Control -- 4 Expression Learning -- 4.1 Network Architecture -- 4.2 Training Data Generation -- 4.3 Network Training -- 4.4 Expression Transfer Pipeline -- 5 Experiments and Results -- 5.1 Facial Expression Datasets -- 5.2 Action Units and Muscle Activations -- 5.3 Head Orientation -- 5.4 Facial Expression Transfer -- 6 Conclusion and Future Work -- References -- Segmentation -- Synthesized Image Datasets: Towards an Annotation-Free Instance Segmentation Strategy -- 1 Introduction -- 2 Related Work -- 3 Proposed Approach -- 3.1 Segmentation Algorithm -- 3.2 Synthesized Image Generation -- 4 Experimental Results -- 4.1 Case Study -- 4.2 Free Annotation Results -- 5 Conclusions -- References -- Holistically-Nested Structure-Aware Graph Neural Network for Road Extraction -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Road Border Detection -- 3.2 Road Structure Aware GNN -- 3.3 Element-Wise Attention -- 3.4 Joint Multi-task Training -- 4 Experimental Results -- 4.1 Evaluation Metrics -- 4.2 Results -- 5 Conclusions -- References -- Extraction and Merging of Stroke Structure of Chinese Characters -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 The Path Network -- 3.2 Pixel Selection for Path Net -- 3.3 Stroke Merging Algorithm -- 4 Experiment Results -- 5 Conclusion -- References -- Analysis of Multi-temporal Image Series for the Preventive Conservation of Varnished Wooden Surfaces -- 1 Introduction -- 2 Related Works. 2.1 Change and Damage Detection -- 2.2 A-Contrario Framework -- 3 Proposed Approach -- 3.1 Distance Matrix -- 3.2 Number of False Alarms -- 3.3 Maximal Clusters -- 4 Experiments -- 4.1 Dataset -- 4.2 Results -- 5 Conclusions -- References -- Visualization -- Evaluating User Interfaces for a Driver Guidance System to Support Stationary Wireless Charging of Electric Vehicles -- 1 Introduction -- 2 Related Work -- 3 System -- 3.1 Goals -- 3.2 Overview -- 3.3 Visualization Types -- 3.4 Information Output Setup -- 4 User Study -- 4.1 Test Environment -- 4.2 Task -- 4.3 Data Acquisition -- 4.4 Results -- 5 Discussion -- 5.1 Precision -- 5.2 User Experience -- 5.3 Time -- 5.4 Observations -- 6 Conclusions -- References -- MOBA Coach: Exploring and Analyzing Multiplayer Online Battle Arena Data -- 1 Introduction -- 2 Related Work -- 3 MOBA Coach Tool -- 4 Evaluation -- 4.1 Analysis of the Results -- 4.2 Discussion of the Results -- 5 Conclusion and Future Work -- References -- JobNet: 2D and 3D Visualization for Temporal and Structural Association in High-Performance Computing System -- 1 Introduction -- 2 Related Work -- 3 Design and Implementation -- 3.1 Terms and Definitions -- 3.2 Design Rationale -- 4 Case Study -- 4.1 JobNet2D -- 4.2 JobNet3D -- 5 Conclusion -- References -- Evaluation and Selection of Autoencoders for Expressive Dimensionality Reduction of Spatial Ensembles -- 1 Introduction -- 2 Related Work -- 3 Study Setup, Metrics and Selection -- 4 Evaluation -- 5 Discussion and Outlook -- References -- Data-Driven Estimation of Temporal-Sampling Errors in Unsteady Flows*-8pt -- 1 Introduction -- 2 Related Work -- 3 Temporal Subsampling Errors in Pathlines -- 3.1 Temporal Subsampling of Simulated Unsteady Flows -- 3.2 Data-Driven Modeling of Errors -- 4 Validation and Results -- 4.1 2D Flow Past a Cylinder -- 4.2 3D Lifted Ethylene Jet Flame. 5 Conclusion -- References -- Applications -- ReGenMorph: Visibly Realistic GAN Generated Face Morphing Attacks by Attack Re-generation -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 The ReGenMorph Face Morphing Pipeline -- 3.2 Creating ReGenMorph Morphing Attacks -- 4 Experimental Setup -- 4.1 Database -- 4.2 Vulnerability Analyses -- 4.3 Detectability Analyses -- 5 Results -- 5.1 ReGenMorph Image Appearance -- 5.2 Vulnerability of Face Recognition to ReGenMorph -- 5.3 Detectability of ReGenMorph -- 6 Conclusion -- References -- Car Pose Estimation Through Wheel Detection -- 1 Introduction -- 2 Related Work -- 3 Wheel Detection Techniques -- 4 Pose Estimation -- 5 Evaluation -- 5.1 Evaluation Datasets -- 5.2 Algorithm Parameterization -- 5.3 Evaluation Metrics -- 5.4 Wheel Detection Accuracy and Time Performance -- 5.5 Pose Estimation Accuracy -- 6 Conclusion and Future Work -- References -- Improving Automatic Quality Inspection in the Automotive Industry by Combining Simulated and Real Data -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 Baseline -- 3.2 CycleGAN with Semantic Consistency -- 3.3 Detection System's Improvements -- 4 Experiments -- 5 Results and Discussion -- 5.1 Domain Mapping -- 5.2 Detector Fine-Tuning -- 6 Conclusion and Future Work -- References -- PW-MAD: Pixel-Wise Supervision for Generalized Face Morphing Attack Detection*-8pt -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 The Proposed PW-MAD -- 3.2 Baselines -- 4 Experimental Setup -- 4.1 The Dataset -- 4.2 Experiments and Evaluation Metrics -- 5 Results and Discussion -- 6 Conclusion -- References -- Integration of a BCI with a Hand Tracking System and a Motorized Robotic Arm to Improve Decoding of Brain Signals Related to Hand and Finger Movements -- 1 Introduction -- 2 System Assembly -- 3 Use-Cases -- 4 Conclusion -- References. Deep Learning II. |
| Record Nr. | UNINA-9910512174103321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in Visual Computing : 16th International Symposium, ISVC 2021, Virtual Event, October 4-6, 2021, Proceedings, Part II / / edited by George Bebis, Vassilis Athitsos, Tong Yan, Manfred Lau, Frederick Li, Conglei Shi, Xiaoru Yuan, Christos Mousas, Gerd Bruder
| Advances in Visual Computing : 16th International Symposium, ISVC 2021, Virtual Event, October 4-6, 2021, Proceedings, Part II / / edited by George Bebis, Vassilis Athitsos, Tong Yan, Manfred Lau, Frederick Li, Conglei Shi, Xiaoru Yuan, Christos Mousas, Gerd Bruder |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 |
| Descrizione fisica | 1 online resource (555 pages) |
| Disciplina | 006.6 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Pattern recognition systems
Computer vision Artificial intelligence Computer engineering Computer networks Automated Pattern Recognition Computer Vision Artificial Intelligence Computer Engineering and Networks |
| ISBN | 3-030-90436-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Keynote Talks -- Embodied Perception in-the-Wild -- Design Tools for Material Appearance -- Guidance-Enriched Visual Analytics: Challenges and Opportunities -- Learning and Accruing Knowledge over Time Using Modular Architectures -- Combining Brain-Computer Interfaces and Virtual Reality: Novel 3D Interactions and Promising Applications -- Direct Estimation of Appearance Models for Image Segmentation -- Contents - Part II -- Contents - Part I -- ST: Medical Image Analysis -- Video-Based Hand Tracking for Screening Cervical Myelopathy -- 1 Introduction -- 2 Related Work -- 2.1 Development of Medical Treatments for Cervical Myelopathy -- 2.2 Expansion of 10-Second Grip and Release Test -- 2.3 Automatic Screening Methods for Various Diseases -- 3 Method Design -- 3.1 Recording Grip and Release Test -- 3.2 Image Processing -- 3.3 Pre-processing of the Data -- 3.4 Two-Class Classification -- 4 Experiments -- 4.1 Overview -- 4.2 Validation for Each Finger and Feature Value -- 4.3 Validation for the Selected Components -- 5 Discussion -- 5.1 Consideration of Validation Results -- 5.2 Comparison with Other Screening Methods -- 5.3 Limitations and Future Work -- 6 Conclusion -- References -- NeoUNet: Towards Accurate Colon Polyp Segmentation and Neoplasm Detection -- 1 Introduction -- 2 Related Work -- 3 Polyp Segmentation and Neoplasm Detection -- 4 NeoUNet -- 4.1 Architecture -- 4.2 Loss Function -- 5 Experiments and Discussion -- 5.1 Benchmark Dataset -- 5.2 Experiment Setup -- 5.3 Results and Discussion -- 6 Conclusion -- References -- Patch-Based Convolutional Neural Networks for TCGA-BRCA Breast Cancer Classification -- 1 Introduction -- 2 Related Literature -- 3 Methodology -- 3.1 Dataset -- 3.2 Preprocessing -- 3.3 Patch Extraction -- 3.4 Patch Filtering -- 3.5 Patch Classification -- 3.6 Patch Aggregation.
3.7 Dataset Augmentation -- 4 Results and Discussion -- 4.1 Whole Slide Image Classification -- 4.2 Patch-Level and Slide-Level Classification After Grid Approach -- 4.3 Patch-Level and Slide-Level Classification After Nuclei-Guided Filtering -- 4.4 Voting Methods -- 4.5 Comparison to Related Studies -- 5 Conclusions -- References -- CT Perfusion Imaging of the Brain with Machine Learning -- 1 Introduction -- 2 Methods -- 2.1 Overview -- 2.2 Dataset -- 2.3 Pre-processing -- 2.4 Training and Deployment -- 3 Experiments -- 4 Discussion -- 5 Conclusion -- References -- Analysis of Macular Thickness Deviation Maps for Diagnosis of Glaucoma -- 1 Introduction -- 2 Methods -- 2.1 Macular OCT Imaging -- 2.2 Macular Deviation Map Processing -- 2.3 Dataset Overview -- 2.4 Machine Learning for Feature Evaluation -- 3 Results and Discussions -- 4 Conclusions -- References -- Pattern Recognition -- Variational Conditional Dependence Hidden Markov Models for Skeleton-Based Action Recognition -- 1 Introduction -- 2 Proposed Model -- 2.1 Model Definition -- 2.2 Model Training -- 2.3 Inference -- 3 Experimental Evaluation -- 3.1 Experimental Details -- 3.2 Parameter Initialization and Hyperparameter Selection -- 3.3 States, Mixtures and Temporal Dependencies -- 3.4 Experimental Results -- 3.5 Missing Values -- 4 Conclusions -- References -- The Unreasonable Effectiveness of the Final Batch Normalization Layer -- 1 Introduction -- 2 Background -- 3 Previous Findings and Existing Hypotheses -- 3.1 Adding a Final Batch Norm Layer Before the Output Layer -- 3.2 Experimentation on PlantVillage Dataset Subject to Different Configurations -- 3.3 Derived Hypotheses -- 4 Implementation Details and Experimental Results -- 4.1 Removing the Additional BN Layer During Inference (H-1) -- 4.2 Impact Level Regarding the Imbalance Ratio (H-2) and the Batch Size (H-3). 4.3 Experimentation on the MNIST Dataset: The Impact of Final BN Layer in Basic CNNs and FC Networks [(H-4),(H-5),(H-6)] -- 5 Discussion -- 6 Conclusions -- References -- Video Analysis and Event Recognition -- Cross Your Body: A Cognitive Assessment System for Children -- 1 Introduction -- 2 Related Work -- 3 Data Acquisition and Protocol Definition -- 4 System Definition -- 4.1 Feature Extraction -- 4.2 Action Segmentation -- 4.3 Analysis -- 4.4 Conclusion -- References -- Privacy-Aware Anomaly Detection Using Semantic Segmentation -- 1 Introduction -- 2 Related Work -- 2.1 Custom Feature Methods -- 2.2 Deep Learning Methods -- 2.3 Object-Centric Methods -- 2.4 Privacy Preserving Anomaly Detection -- 3 The Proposed System -- 3.1 Segmentation Model Comparison -- 3.2 Quantitative Comparison of Models -- 3.3 Segmentation Results -- 3.4 Processing -- 4 Results and Discussion -- 4.1 Anomaly Detection Evaluation Metrics -- 4.2 Global Accuracy -- 4.3 Anomaly Specific Accuracy -- 5 Conclusion -- References -- Learning Self-supervised Audio-Visual Representations for Sound Recommendations -- 1 Introduction -- 2 Related Work -- 3 Datasets -- 4 Self-supervised Audio-Visual Representation Learning -- 4.1 Baseline Model -- 4.2 Attention-Based Model -- 4.3 Unlabeled Contrastive Learning -- 5 Performance Evaluation -- 5.1 Audio-Visual Correlation Performance -- 5.2 Sound Recommendation Performance -- 6 Conclusions -- References -- Poster -- Security Automation Through a Multi-processing Real-Time System for the Re-identification of Persons -- 1 Introduction -- 2 Background -- 2.1 Person Detection and Tracking -- 2.2 Person Re-identification -- 3 Research Methodology -- 3.1 Prototype Pipeline -- 3.2 Datasets -- 3.3 Person Detection and Tracking -- 3.4 Vehicle Detection and Assignment -- 3.5 Clothes Detection -- 3.6 Clothes Color Detection. 3.7 Histogram Processing and Correlation Metrics -- 3.8 Final Stage - Re-identification Using Multiple Features -- 3.9 Ethical Considerations -- 4 Findings and Discussion of Results -- 4.1 Single Person Comparison from 2 Separate Feeds -- 4.2 Multiple Persons Comparison from 2 Separate Feeds -- 5 Conclusion -- References -- A Method for Transferring Robot Motion Parameters Using Functional Attributes of Parts -- 1 Introduction -- 2 Problem Formulation -- 3 Parts Function -- 3.1 ``Part Functions'' of Industrial Parts -- 3.2 Robot Motion Parameters for Assembly -- 3.3 Basic Idea of Proposed Method Regarding Functional Attributes of Parts -- 4 Proposed Method for Transferring Robot Motion Parameters -- 4.1 Module for Functional-Attribute Recognition -- 4.2 Module for Transferring of Grasping and Action Points -- 4.3 Transferring Operating Pattern -- 5 Experiments on Transferring Robot Motion Parameters -- 5.1 Setup -- 5.2 Experimental Results -- 6 Conclusion -- References -- Uncooperative Satellite 6D Pose Estimation with Relative Depth Information -- 1 Introduction -- 2 Related Works -- 3 Approach -- 3.1 Image Simulation -- 3.2 Network Architecture -- 4 Experiment -- 5 Conclusion and Future Work -- References -- Non-homogeneous Haze Removal Through a Multiple Attention Module Architecture -- 1 Introduction -- 2 Related Work -- 3 Proposed Approach -- 3.1 Architecture -- 3.2 Loss Functions -- 3.3 Instance Normalization -- 4 Experimental Results -- 4.1 Datasets -- 4.2 Training Settings -- 4.3 Comparisons -- 5 Conclusions -- References -- Vehicle Detection and Tracking from Surveillance Cameras in Urban Scenes -- 1 Introduction -- 2 Background and Related Works -- 3 Proposed Solution -- 4 Results and Discussion -- 5 Conclusion -- References -- Towards the Creation of Spontaneous Datasets Based on Youtube Reaction Videos -- 1 Introduction -- 2 Related Work. 3 Proposed Method -- 3.1 Obtaining Data -- 3.2 Pre-processing and Frames Extraction -- 3.3 Faces and Facial Landmarks Extraction -- 3.4 Most Intense Moment (MIM) -- 3.5 Facial Emotion Recognition -- 3.6 Emotion Recognition Analysis -- 3.7 Dataset Generated -- 4 Final Considerations -- References -- Automated Bite-block Detection to Distinguish Colonoscopy from Upper Endoscopy Using Deep Learning -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Image Preprocessing -- 3.2 Bite-block CNN and Tongue CNN -- 3.3 Classifications of Bite-block and Tongue Patches -- 3.4 Detection of Upper Endoscopy Video -- 4 Experiments and Results -- 4.1 Datasets -- 4.2 Training and Testing -- 4.3 Performance Metrics and Accuracy Comparison -- 4.4 Effects of Hue and Saturation -- 5 Conclusion -- References -- How Does Heterogeneous Label Noise Impact Generalization in Neural Nets? -- 1 Introduction -- 2 Related Works -- 3 Problem Setup -- 3.1 Multi-class Classification -- 3.2 Multi-task Learning -- 3.3 Multi-label Learning -- 4 Experiments and Datasets -- 4.1 Multi-class Classification -- 4.2 Multi-task Learning -- 4.3 Multi-label Learning -- 5 Results -- 5.1 Multi-class Classification -- 5.2 Multi-task Learning -- 5.3 Multi-label Learning -- 6 Discussion -- 7 Conclusion -- References -- A Simple Generative Network -- 1 Introduction -- 2 SGN Proposed Model -- 3 Simulation Results -- 4 Concluding Remarks -- References -- Hyperspectral Video Super-Resolution Using Beta Process and Bayesian Dictionary Learning -- 1 Introduction -- 1.1 Scene Geometry in Hyperspectral Imaging -- 1.2 Hyperspectral Video Registration -- 1.3 Contribution -- 1.4 Paper Organization -- 2 Related Works -- 2.1 Super-Resolution -- 2.2 Hyperspectral Image Analysis -- 2.3 Hyperspectral Image and Video Super-Resolution -- 3 Methodology -- 3.1 Spatial Super-Resolution for a Hyperspectral Video. 3.2 Spectral Video Restoration. |
| Record Nr. | UNINA-9910512174203321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
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 | ||
| ||
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] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
