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Advances in Visual Computing : 18th International Symposium, ISVC 2023, Lake Tahoe, NV, USA, October 16-18, 2023, Proceedings, Part I
| Advances in Visual Computing : 18th International Symposium, ISVC 2023, Lake Tahoe, NV, USA, October 16-18, 2023, Proceedings, Part I |
| Autore | Bebis George |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cham : , : Springer, , 2024 |
| Descrizione fisica | 1 online resource (630 pages) |
| Altri autori (Persone) |
GhiasiGolnaz
FangYi SharfAndrei DongYue WeaverChris LeoZhicheng LaViola JrJoseph J KohliLuv |
| Collana | Lecture Notes in Computer Science Series |
| ISBN | 3-031-47969-6 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Keynote Talks -- Machine Learning for Scientific Data Analysis and Visualization -- Estimating the Structure and Motion of Biomolecules at Atomic Resolutions -- Curriculum Learning and Active Learning, for Visual Object Recognition when Data is Scarce -- Have We Solved Image Correspondences? -- Visual Content Manipulation by Learning Generative Models -- Lights, Camera, Animation! Adaptive Simulation Methods for Training and Entertainment -- Beyond the Specs: A Computational and Human-Centered Approach to Wearability in AR/VR -- Contents - Part I -- Contents - Part II -- ST: Biomedical Image Analysis Techniques for Cancer Detection, Diagnosis and Management -- Hybrid Region and Pixel-Level Adaptive Loss for Mass Segmentation on Whole Mammography Images -- 1 Introduction -- 2 Related Work -- 2.1 Mass Segmentation on Whole Mammograms -- 2.2 Loss for Medical Image Segmentation -- 3 Methodology -- 3.1 Hybrid Pixel-Level Loss -- 3.2 Hybrid Region-Level Loss -- 3.3 Density-Adaptive Sample-Level Prioritizing Loss -- 4 Experimental Results -- 4.1 Datasets -- 4.2 Evaluation Metrics -- 4.3 Comparison with State-of-the-Art Methods -- 5 Conclusion -- References -- Deep Learning Based GABA Edited-MRS Signal Reconstruction -- 1 Introduction -- 2 Methods -- 2.1 Dataset -- 2.2 J-Difference Spectrum -- 2.3 Dual Branch Self-Attention Neural Network -- 2.4 Evaluation Metrics -- 3 Results and Discussion -- 4 Conclusion -- References -- Investigating the Impact of Attention on Mammogram Classification -- 1 Introduction -- 2 Data and Methods -- 2.1 Data Selection and Preprocessing -- 2.2 Selection of Models -- 2.3 Selection of Attention Methods -- 2.4 Training and Testing Process -- 3 Results and Discussion -- 3.1 Impact of Attention on CNN Performance -- 3.2 Impact of Model Architecture on Performance Differences.
3.3 Impact of Attention on Resolution -- 3.4 Impact of Attention on Abnormality Type -- 3.5 Relationship Between Model Activation and AU-ROC -- 4 Conclusions -- References -- ReFit: A Framework for Refinement of Weakly Supervised Semantic Segmentation Using Object Border Fitting for Medical Images -- 1 Introduction -- 2 Our ReFit Framework -- 2.1 Unsupervised Segment Detection -- 2.2 Class Activation Map - CAM -- 2.3 The BoundaryFit Module -- 3 Results and Discussion -- 3.1 Ablation Studies -- 4 Conclusion -- References -- A Data-Centric Approach for Pectoral Muscle Deep Learning Segmentation Enhancements in Mammography Images -- 1 Introduction -- 2 Related Work -- 3 Mammography Segmentation -- 3.1 Dataset -- 3.2 Model Training -- 3.3 Drawbacks -- 4 Data-Centric Model Optimization -- 4.1 Stage I: Annotation Correction -- 4.2 Stage II: Downsampling -- 5 Results -- 5.1 Evaluation Metrics -- 5.2 Evaluated Training Datasets -- 5.3 Intersection over Union Evaluation -- 5.4 Classification Metrics for Pectoral Muscle Detection in CC View -- 6 Conclusion -- References -- Visualization -- Visualizing Multimodal Time Series at Scale -- 1 Introduction -- 2 Related Work -- 3 Overview Scenario -- 4 Detail Methods and Implementation -- 4.1 Time Series Dataset -- 4.2 Exploiting Elasticsearch for Fast Search and Big Query -- 4.3 Visualizing Time Series -- 5 Exploring UMAFall Dataset with TimeXplore -- 6 Conclusions and Future Work -- References -- Hybrid Tree Visualizations for Analysis of Gerrymandering -- 1 Introduction -- 2 Related Work -- 3 Gerrymandering -- 4 Data Model in Gerrymandering -- 5 Visual Design -- 6 Analysis Examples -- 6.1 Evaluating the Efficiency Gap -- 6.2 Assessing Electoral Competition -- 7 Conclusion -- References -- ArcheryVis: A Tool for Analyzing and Visualizing Archery Performance Data -- 1 Introduction -- 2 Related Work. 2.1 Archery Performance Analysis -- 2.2 Archery Scoring Apps -- 3 Data Collection, Processing, and Analysis -- 3.1 Data Collection -- 3.2 Ring and Center Detection -- 3.3 Shot Detection and Calibration -- 3.4 Scoring and Statistical Measures -- 4 Visual Interface and Interaction -- 5 Results and Discussion -- 5.1 Brushing and Filtering -- 5.2 Trainee Comparison -- 5.3 Statistical Measure as Performance Indicator -- 5.4 Empirical Evaluation -- 5.5 Limitations -- 6 Conclusions and Future Work -- References -- Spiro: Order-Preserving Visualization in High Performance Computing Monitoring -- 1 Introduction -- 2 Related Work -- 2.1 Spiral Layout in Visualization -- 2.2 Monitoring with Spiral Layout -- 3 Monitoring Tasks -- 4 Spiro Design -- 4.1 Design Rationales -- 4.2 Visual Encoding -- 5 Case Studies -- 5.1 Clustering on Compute Servers -- 5.2 Exploring Usage Behavior -- 6 Conclusion and Future Work -- References -- From Faces to Volumes - Measuring Volumetric Asymmetry in 3D Facial Palsy Scans -- 1 Introduction -- 2 Related Work -- 3 Data Acquisition -- 4 Methods -- 4.1 3D Landmark Extraction for Facial Palsy Patients -- 4.2 Radial Curves -- 4.3 Lateral Face Mesh Generation -- 4.4 Volume Estimation for Lateral Face Sides -- 4.5 Volumetric Difference Visualization -- 5 Volume Analysis During Dynamic Movements -- 6 Conclusions and Future Work -- References -- Video Analysis and Event Recognition -- Comparison of Autoencoder Models for Unsupervised Representation Learning of Skeleton Sequences -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 Proposed Methods -- 4 Experiments -- 4.1 Datasets -- 4.2 Results Analysis and Comparisons -- 5 Conclusion and Future Works -- References -- Local and Global Context Reasoning for Spatio-Temporal Action Localization -- 1 Introduction -- 2 Related Works -- 3 Proposed Method -- 3.1 Overall Pipeline. 3.2 Near-Actor Relation Network -- 4 Experiments on JHMDB21 -- 4.1 Implementation Details -- 4.2 Comparison on JHMDB21 -- 4.3 Ablation Study -- 4.4 Qualitative Results -- 5 Experiments on AVA -- 5.1 Implementation Details -- 5.2 Comparison on AVA -- 6 Conclusion -- References -- Zero-Shot Video Moment Retrieval Using BLIP-Based Models -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Computing Image and Text Embeddings -- 3.2 Sparse Frame-Sampling Strategies -- 3.3 Moment-Query Matching -- 4 Experiments -- 5 Results and Discussion -- 6 Conclusions and Future Work -- References -- Self-supervised Representation Learning for Fine Grained Human Hand Action Recognition in Industrial Assembly Lines -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Model Architecture -- 3.2 Masking Method -- 4 Experiments -- 4.1 Datasets -- 4.2 Model Training Environment -- 4.3 Self-supervised Pretraining and Downstream Task -- 5 Results and Analysis -- 5.1 Results Self-supervised Learning -- 5.2 Results Downstream Task -- 5.3 Analysis -- 6 Conclusion and Outlook -- References -- ST: Innovations in Computer Vision & -- Machine Learning for Critical & -- Civil Infrastructures -- Pretext Tasks in Bridge Defect Segmentation Within a ViT-Adapter Framework -- 1 Introduction -- 2 Methods -- 2.1 ViT-Adapter Model -- 2.2 Datasets -- 2.3 Supervised Learning (SL) Pre-training -- 2.4 Self- And Semi-Supervised Learning (SSL) Pre-training -- 2.5 Training Parameters -- 3 Results and Discussion -- 4 Conclusion -- References -- A Few-Shot Attention Recurrent Residual U-Net for Crack Segmentation -- 1 Introduction -- 1.1 Current Limitations and Our Contribution -- 2 Proposed Architecture -- 2.1 R2AU-Net Architecture for Road Crack Segmentation -- 2.2 Few-Shot Learning for Segmentation Refinement -- 3 Experimental Setup and Results -- 3.1 Dataset Description. 3.2 Comparative Algorithms and Training Configuration -- 3.3 Experiments and Comparisons -- 4 Conclusions -- References -- Efficient Resource Provisioning in Critical Infrastructures Based on Multi-Agent Rollout Enabled by Deep Q-Learning -- 1 Introduction -- 2 Related Work -- 3 Workload Management in Critical Infrastructures -- 3.1 Infrastructure Model -- 3.2 Problem Formulation -- 3.3 Deterministic Markov Decision Process Model -- 3.4 Multi-Agent Rollout Enabled by Deep Q-Learning -- 4 Simulation Experiments -- 4.1 Experimental Setup -- 4.2 Evaluation Results -- 5 Conclusions -- References -- Video-Based Recognition of Aquatic Invasive Species Larvae Using Attention-LSTM Transformer -- 1 Introduction -- 1.1 Attention-LSTM -- 2 Related Work -- 3 Proposed Method -- 3.1 Model Architecture -- 3.2 Attention-LSTM Layer -- 3.3 Model Variations -- 4 Invasive Species Dataset -- 5 Empirical Evaluation -- 6 Conclusion -- References -- ST: Generalization in Visual Machine Learning -- Latent Space Navigation for Face Privacy: A Case Study on the MNIST Dataset -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 4 Experimental Result -- 5 Future Work -- 6 Conclusion -- References -- Domain Generalization for Foreground Segmentation Using Federated Learning -- 1 Introduction -- 2 Related Work -- 3 Proposed Work -- 3.1 Model Architecture -- 3.2 Training Technique -- 4 Experiments -- 4.1 Datasets -- 4.2 Implementation Details -- 4.3 Traditional Foreground Segmentation Experiment -- 4.4 Domain Generalization Experiment -- 4.5 Few-Shot Experiment -- 5 Conclusion and Future Work -- References -- Probabilistic Local Equivalence Certification for Robustness Evaluation -- 1 Introduction -- 2 Related Work -- 3 Probabilistic Local Equivalence Certification -- 3.1 Probabilistic Local Equivalence Certification -- 3.2 When Labels are Available. 3.3 The Case of Classification. |
| Record Nr. | UNISA-996565867203316 |
Bebis George
|
||
| Cham : , : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Advances in Visual Computing : 18th International Symposium, ISVC 2023, Lake Tahoe, NV, USA, October 16-18, 2023, Proceedings, Part I
| Advances in Visual Computing : 18th International Symposium, ISVC 2023, Lake Tahoe, NV, USA, October 16-18, 2023, Proceedings, Part I |
| Autore | Bebis George |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cham : , : Springer, , 2024 |
| Descrizione fisica | 1 online resource (630 pages) |
| Altri autori (Persone) |
GhiasiGolnaz
FangYi SharfAndrei DongYue WeaverChris LeoZhicheng LaViola JrJoseph J KohliLuv |
| Collana | Lecture Notes in Computer Science Series |
| ISBN | 3-031-47969-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Keynote Talks -- Machine Learning for Scientific Data Analysis and Visualization -- Estimating the Structure and Motion of Biomolecules at Atomic Resolutions -- Curriculum Learning and Active Learning, for Visual Object Recognition when Data is Scarce -- Have We Solved Image Correspondences? -- Visual Content Manipulation by Learning Generative Models -- Lights, Camera, Animation! Adaptive Simulation Methods for Training and Entertainment -- Beyond the Specs: A Computational and Human-Centered Approach to Wearability in AR/VR -- Contents - Part I -- Contents - Part II -- ST: Biomedical Image Analysis Techniques for Cancer Detection, Diagnosis and Management -- Hybrid Region and Pixel-Level Adaptive Loss for Mass Segmentation on Whole Mammography Images -- 1 Introduction -- 2 Related Work -- 2.1 Mass Segmentation on Whole Mammograms -- 2.2 Loss for Medical Image Segmentation -- 3 Methodology -- 3.1 Hybrid Pixel-Level Loss -- 3.2 Hybrid Region-Level Loss -- 3.3 Density-Adaptive Sample-Level Prioritizing Loss -- 4 Experimental Results -- 4.1 Datasets -- 4.2 Evaluation Metrics -- 4.3 Comparison with State-of-the-Art Methods -- 5 Conclusion -- References -- Deep Learning Based GABA Edited-MRS Signal Reconstruction -- 1 Introduction -- 2 Methods -- 2.1 Dataset -- 2.2 J-Difference Spectrum -- 2.3 Dual Branch Self-Attention Neural Network -- 2.4 Evaluation Metrics -- 3 Results and Discussion -- 4 Conclusion -- References -- Investigating the Impact of Attention on Mammogram Classification -- 1 Introduction -- 2 Data and Methods -- 2.1 Data Selection and Preprocessing -- 2.2 Selection of Models -- 2.3 Selection of Attention Methods -- 2.4 Training and Testing Process -- 3 Results and Discussion -- 3.1 Impact of Attention on CNN Performance -- 3.2 Impact of Model Architecture on Performance Differences.
3.3 Impact of Attention on Resolution -- 3.4 Impact of Attention on Abnormality Type -- 3.5 Relationship Between Model Activation and AU-ROC -- 4 Conclusions -- References -- ReFit: A Framework for Refinement of Weakly Supervised Semantic Segmentation Using Object Border Fitting for Medical Images -- 1 Introduction -- 2 Our ReFit Framework -- 2.1 Unsupervised Segment Detection -- 2.2 Class Activation Map - CAM -- 2.3 The BoundaryFit Module -- 3 Results and Discussion -- 3.1 Ablation Studies -- 4 Conclusion -- References -- A Data-Centric Approach for Pectoral Muscle Deep Learning Segmentation Enhancements in Mammography Images -- 1 Introduction -- 2 Related Work -- 3 Mammography Segmentation -- 3.1 Dataset -- 3.2 Model Training -- 3.3 Drawbacks -- 4 Data-Centric Model Optimization -- 4.1 Stage I: Annotation Correction -- 4.2 Stage II: Downsampling -- 5 Results -- 5.1 Evaluation Metrics -- 5.2 Evaluated Training Datasets -- 5.3 Intersection over Union Evaluation -- 5.4 Classification Metrics for Pectoral Muscle Detection in CC View -- 6 Conclusion -- References -- Visualization -- Visualizing Multimodal Time Series at Scale -- 1 Introduction -- 2 Related Work -- 3 Overview Scenario -- 4 Detail Methods and Implementation -- 4.1 Time Series Dataset -- 4.2 Exploiting Elasticsearch for Fast Search and Big Query -- 4.3 Visualizing Time Series -- 5 Exploring UMAFall Dataset with TimeXplore -- 6 Conclusions and Future Work -- References -- Hybrid Tree Visualizations for Analysis of Gerrymandering -- 1 Introduction -- 2 Related Work -- 3 Gerrymandering -- 4 Data Model in Gerrymandering -- 5 Visual Design -- 6 Analysis Examples -- 6.1 Evaluating the Efficiency Gap -- 6.2 Assessing Electoral Competition -- 7 Conclusion -- References -- ArcheryVis: A Tool for Analyzing and Visualizing Archery Performance Data -- 1 Introduction -- 2 Related Work. 2.1 Archery Performance Analysis -- 2.2 Archery Scoring Apps -- 3 Data Collection, Processing, and Analysis -- 3.1 Data Collection -- 3.2 Ring and Center Detection -- 3.3 Shot Detection and Calibration -- 3.4 Scoring and Statistical Measures -- 4 Visual Interface and Interaction -- 5 Results and Discussion -- 5.1 Brushing and Filtering -- 5.2 Trainee Comparison -- 5.3 Statistical Measure as Performance Indicator -- 5.4 Empirical Evaluation -- 5.5 Limitations -- 6 Conclusions and Future Work -- References -- Spiro: Order-Preserving Visualization in High Performance Computing Monitoring -- 1 Introduction -- 2 Related Work -- 2.1 Spiral Layout in Visualization -- 2.2 Monitoring with Spiral Layout -- 3 Monitoring Tasks -- 4 Spiro Design -- 4.1 Design Rationales -- 4.2 Visual Encoding -- 5 Case Studies -- 5.1 Clustering on Compute Servers -- 5.2 Exploring Usage Behavior -- 6 Conclusion and Future Work -- References -- From Faces to Volumes - Measuring Volumetric Asymmetry in 3D Facial Palsy Scans -- 1 Introduction -- 2 Related Work -- 3 Data Acquisition -- 4 Methods -- 4.1 3D Landmark Extraction for Facial Palsy Patients -- 4.2 Radial Curves -- 4.3 Lateral Face Mesh Generation -- 4.4 Volume Estimation for Lateral Face Sides -- 4.5 Volumetric Difference Visualization -- 5 Volume Analysis During Dynamic Movements -- 6 Conclusions and Future Work -- References -- Video Analysis and Event Recognition -- Comparison of Autoencoder Models for Unsupervised Representation Learning of Skeleton Sequences -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 Proposed Methods -- 4 Experiments -- 4.1 Datasets -- 4.2 Results Analysis and Comparisons -- 5 Conclusion and Future Works -- References -- Local and Global Context Reasoning for Spatio-Temporal Action Localization -- 1 Introduction -- 2 Related Works -- 3 Proposed Method -- 3.1 Overall Pipeline. 3.2 Near-Actor Relation Network -- 4 Experiments on JHMDB21 -- 4.1 Implementation Details -- 4.2 Comparison on JHMDB21 -- 4.3 Ablation Study -- 4.4 Qualitative Results -- 5 Experiments on AVA -- 5.1 Implementation Details -- 5.2 Comparison on AVA -- 6 Conclusion -- References -- Zero-Shot Video Moment Retrieval Using BLIP-Based Models -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Computing Image and Text Embeddings -- 3.2 Sparse Frame-Sampling Strategies -- 3.3 Moment-Query Matching -- 4 Experiments -- 5 Results and Discussion -- 6 Conclusions and Future Work -- References -- Self-supervised Representation Learning for Fine Grained Human Hand Action Recognition in Industrial Assembly Lines -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Model Architecture -- 3.2 Masking Method -- 4 Experiments -- 4.1 Datasets -- 4.2 Model Training Environment -- 4.3 Self-supervised Pretraining and Downstream Task -- 5 Results and Analysis -- 5.1 Results Self-supervised Learning -- 5.2 Results Downstream Task -- 5.3 Analysis -- 6 Conclusion and Outlook -- References -- ST: Innovations in Computer Vision & -- Machine Learning for Critical & -- Civil Infrastructures -- Pretext Tasks in Bridge Defect Segmentation Within a ViT-Adapter Framework -- 1 Introduction -- 2 Methods -- 2.1 ViT-Adapter Model -- 2.2 Datasets -- 2.3 Supervised Learning (SL) Pre-training -- 2.4 Self- And Semi-Supervised Learning (SSL) Pre-training -- 2.5 Training Parameters -- 3 Results and Discussion -- 4 Conclusion -- References -- A Few-Shot Attention Recurrent Residual U-Net for Crack Segmentation -- 1 Introduction -- 1.1 Current Limitations and Our Contribution -- 2 Proposed Architecture -- 2.1 R2AU-Net Architecture for Road Crack Segmentation -- 2.2 Few-Shot Learning for Segmentation Refinement -- 3 Experimental Setup and Results -- 3.1 Dataset Description. 3.2 Comparative Algorithms and Training Configuration -- 3.3 Experiments and Comparisons -- 4 Conclusions -- References -- Efficient Resource Provisioning in Critical Infrastructures Based on Multi-Agent Rollout Enabled by Deep Q-Learning -- 1 Introduction -- 2 Related Work -- 3 Workload Management in Critical Infrastructures -- 3.1 Infrastructure Model -- 3.2 Problem Formulation -- 3.3 Deterministic Markov Decision Process Model -- 3.4 Multi-Agent Rollout Enabled by Deep Q-Learning -- 4 Simulation Experiments -- 4.1 Experimental Setup -- 4.2 Evaluation Results -- 5 Conclusions -- References -- Video-Based Recognition of Aquatic Invasive Species Larvae Using Attention-LSTM Transformer -- 1 Introduction -- 1.1 Attention-LSTM -- 2 Related Work -- 3 Proposed Method -- 3.1 Model Architecture -- 3.2 Attention-LSTM Layer -- 3.3 Model Variations -- 4 Invasive Species Dataset -- 5 Empirical Evaluation -- 6 Conclusion -- References -- ST: Generalization in Visual Machine Learning -- Latent Space Navigation for Face Privacy: A Case Study on the MNIST Dataset -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 4 Experimental Result -- 5 Future Work -- 6 Conclusion -- References -- Domain Generalization for Foreground Segmentation Using Federated Learning -- 1 Introduction -- 2 Related Work -- 3 Proposed Work -- 3.1 Model Architecture -- 3.2 Training Technique -- 4 Experiments -- 4.1 Datasets -- 4.2 Implementation Details -- 4.3 Traditional Foreground Segmentation Experiment -- 4.4 Domain Generalization Experiment -- 4.5 Few-Shot Experiment -- 5 Conclusion and Future Work -- References -- Probabilistic Local Equivalence Certification for Robustness Evaluation -- 1 Introduction -- 2 Related Work -- 3 Probabilistic Local Equivalence Certification -- 3.1 Probabilistic Local Equivalence Certification -- 3.2 When Labels are Available. 3.3 The Case of Classification. |
| Record Nr. | UNINA-9910767585603321 |
|
Bebis George
|
||
| Cham : , : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in Visual Computing [[electronic resource] ] : 18th International Symposium, ISVC 2023, Lake Tahoe, NV, USA, October 16–18, 2023, Proceedings, Part II / / edited by George Bebis, Golnaz Ghiasi, Yi Fang, Andrei Sharf, Yue Dong, Chris Weaver, Zhicheng Leo, Joseph J. LaViola Jr., Luv Kohli
| Advances in Visual Computing [[electronic resource] ] : 18th International Symposium, ISVC 2023, Lake Tahoe, NV, USA, October 16–18, 2023, Proceedings, Part II / / edited by George Bebis, Golnaz Ghiasi, Yi Fang, Andrei Sharf, Yue Dong, Chris Weaver, Zhicheng Leo, Joseph J. LaViola Jr., Luv Kohli |
| Autore | Bebis George |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (506 pages) |
| Disciplina | 006 |
| Altri autori (Persone) |
GhiasiGolnaz
FangYi SharfAndrei DongYue WeaverChris LeoZhicheng LaViola JrJoseph J KohliLuv |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Image processing - Digital techniques
Computer vision Computer Imaging, Vision, Pattern Recognition and Graphics |
| ISBN | 3-031-47966-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Virtual Reality -- A Pilot Study Comparing User Interactions Between Augmented and Virtual Reality -- Synthesizing Play-Ready VR Scenes with Natural Language Prompts through GPT API -- Emergent Individual Factors for AR Education and Training -- Segmentation -- ISLE: A Framework for Image Level Semantic Segmentation Ensemble -- Particulate Mapping Centerline Extraction (PMCE), a Novel Centerline Extraction Algorithm Based on Patterns in the Spatial Distribution of Aggregates -- Evaluating Segmentation Approaches on Digitized Herbarium Specimens -- Semantic Scene Filtering for Event Cameras in Long-Term Outdoor Monitoring Scenarios -- SODAWideNet - Salient Object Detection with an Attention augmented Wide Encoder Decoder network without ImageNet pre-training -- Applications -- Foil-Net: Deep Learning-Based Wave Classification for Hydrofoil Surfing -- Inpainting of Depth Images using Deep Neural Networks for Real-Time Applications -- Using 2D and 3D Face Representations to Generate Comprehensive Facial Electromyography Intensity Maps -- Real-world Image Deblurring via Unsupervised Domain Adaptation -- Object Detection and Recognition -- Reliable Matching by Combining Optimal Color and Intensity Information based on Relationships between Target and Surrounding Objects -- Regularized Meta-Training with Embedding Mixup for Improved Few-Shot Learning -- Visual Foreign Object Detection for Wireless Charging of Electric Vehicles -- Deep Representation Learning for License Plate Recognition in Low Quality Video Images -- Optimizing PnP-Algorithms for Limited Point Correspondences Using Spatial Constraints -- Deep Learning -- Unsupervised Deep-Learning Approach for Underwater Image Enhancement -- LaneNet++ : Uncertainty-aware Lane Detection for Autonomous Vehicle -- Task-driven Compression for Collision Encoding based on Depth Images -- Eigenpatches - Adversarial Patches from Principal Components -- Edge-guided Image Inpainting with Transformer -- Poster -- Bayesian Fusion inspired 3D reconstruction via LiDAR-Stereo Camera Pair -- Marimba Mallet Placement Tracker -- DINO-CXR: A Self Supervised Method Based on Vision Transformer for Chest X-Ray Classification -- Social Bias and Image Tagging: Evaluation of Progress in State-of-the-Art Models -- L-TReiD: Logic Tensor Transformer for Re-Identification -- Retinal Disease Diagnosis with a Hybrid ResNet50-LSTM Deep Learning Model -- Pothole Segmentation and Area Estimation with Deep Neural Networks and Unmanned Aerial Vehicles -- Generation method of robot assembly motion considering physicality gap between humans and robots -- A Self-Supervised Pose Estimation Approach for Construction Machines -- Image Quality Improvement of Surveillance Camera Images by Learning Noise Removal Method Using Noise2Noise -- Automating Kernel Size Selection in MRI Reconstruction via a Transparent and Interpretable Search Approach -- Segmentation and Identification of Mediterranean Plant Species -- Exploiting Generative Adversarial Networks in Joint Sensitivity Encoding for Enhanced MRI Reconstruction -- Multisensory Modeling of Tabular Data for Enhanced Perception and Immersive User Experience -- Coping with Bullying Incidents by the Narrative and Multi-modal Interaction in Virtual Reality. |
| Record Nr. | UNINA-9910767583103321 |
|
Bebis George
|
||
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in Visual Computing [[electronic resource] ] : 18th International Symposium, ISVC 2023, Lake Tahoe, NV, USA, October 16–18, 2023, Proceedings, Part II / / edited by George Bebis, Golnaz Ghiasi, Yi Fang, Andrei Sharf, Yue Dong, Chris Weaver, Zhicheng Leo, Joseph J. LaViola Jr., Luv Kohli
| Advances in Visual Computing [[electronic resource] ] : 18th International Symposium, ISVC 2023, Lake Tahoe, NV, USA, October 16–18, 2023, Proceedings, Part II / / edited by George Bebis, Golnaz Ghiasi, Yi Fang, Andrei Sharf, Yue Dong, Chris Weaver, Zhicheng Leo, Joseph J. LaViola Jr., Luv Kohli |
| Autore | Bebis George |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (506 pages) |
| Disciplina | 006 |
| Altri autori (Persone) |
GhiasiGolnaz
FangYi SharfAndrei DongYue WeaverChris LeoZhicheng LaViola JrJoseph J KohliLuv |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Image processing - Digital techniques
Computer vision Computer Imaging, Vision, Pattern Recognition and Graphics |
| ISBN | 3-031-47966-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Virtual Reality -- A Pilot Study Comparing User Interactions Between Augmented and Virtual Reality -- Synthesizing Play-Ready VR Scenes with Natural Language Prompts through GPT API -- Emergent Individual Factors for AR Education and Training -- Segmentation -- ISLE: A Framework for Image Level Semantic Segmentation Ensemble -- Particulate Mapping Centerline Extraction (PMCE), a Novel Centerline Extraction Algorithm Based on Patterns in the Spatial Distribution of Aggregates -- Evaluating Segmentation Approaches on Digitized Herbarium Specimens -- Semantic Scene Filtering for Event Cameras in Long-Term Outdoor Monitoring Scenarios -- SODAWideNet - Salient Object Detection with an Attention augmented Wide Encoder Decoder network without ImageNet pre-training -- Applications -- Foil-Net: Deep Learning-Based Wave Classification for Hydrofoil Surfing -- Inpainting of Depth Images using Deep Neural Networks for Real-Time Applications -- Using 2D and 3D Face Representations to Generate Comprehensive Facial Electromyography Intensity Maps -- Real-world Image Deblurring via Unsupervised Domain Adaptation -- Object Detection and Recognition -- Reliable Matching by Combining Optimal Color and Intensity Information based on Relationships between Target and Surrounding Objects -- Regularized Meta-Training with Embedding Mixup for Improved Few-Shot Learning -- Visual Foreign Object Detection for Wireless Charging of Electric Vehicles -- Deep Representation Learning for License Plate Recognition in Low Quality Video Images -- Optimizing PnP-Algorithms for Limited Point Correspondences Using Spatial Constraints -- Deep Learning -- Unsupervised Deep-Learning Approach for Underwater Image Enhancement -- LaneNet++ : Uncertainty-aware Lane Detection for Autonomous Vehicle -- Task-driven Compression for Collision Encoding based on Depth Images -- Eigenpatches - Adversarial Patches from Principal Components -- Edge-guided Image Inpainting with Transformer -- Poster -- Bayesian Fusion inspired 3D reconstruction via LiDAR-Stereo Camera Pair -- Marimba Mallet Placement Tracker -- DINO-CXR: A Self Supervised Method Based on Vision Transformer for Chest X-Ray Classification -- Social Bias and Image Tagging: Evaluation of Progress in State-of-the-Art Models -- L-TReiD: Logic Tensor Transformer for Re-Identification -- Retinal Disease Diagnosis with a Hybrid ResNet50-LSTM Deep Learning Model -- Pothole Segmentation and Area Estimation with Deep Neural Networks and Unmanned Aerial Vehicles -- Generation method of robot assembly motion considering physicality gap between humans and robots -- A Self-Supervised Pose Estimation Approach for Construction Machines -- Image Quality Improvement of Surveillance Camera Images by Learning Noise Removal Method Using Noise2Noise -- Automating Kernel Size Selection in MRI Reconstruction via a Transparent and Interpretable Search Approach -- Segmentation and Identification of Mediterranean Plant Species -- Exploiting Generative Adversarial Networks in Joint Sensitivity Encoding for Enhanced MRI Reconstruction -- Multisensory Modeling of Tabular Data for Enhanced Perception and Immersive User Experience -- Coping with Bullying Incidents by the Narrative and Multi-modal Interaction in Virtual Reality. |
| Record Nr. | UNISA-996574260103316 |
|
Bebis George
|
||
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||