Advances in visual computing Part 1 / George Bebis, Golnaz Ghiasi, Yi Fang, Andrei Sharf, Yue Dong, Chris Weaver, Zhicheng Leo, Joseph J. LaViola Jr., Luv Kohli, editors
This volume LNCS 14361 and 14362 constitutes the refereed proceedings of the, 16th International Symposium, ISVC 2023, in October 2023, held at Lake Tahoe, NV, USA. The 42 full papers and 13 poster papers were carefully reviewed and selected from 120 submissions. A total of 25 papers were also accepted for oral presentation in special tracks from 34 submissions. The following topical sections followed as: Part 1: ST: Biomedical Image Analysis Techniques for Cancer Detection, Diagnosis and Management; Visualization; Video Analysis and Event Recognition; ST: Innovations in Computer Vision & Machine Learning for Critical & Civil Infrastructures; ST: Generalization in Visual Machine Learning; Computer Graphics; Medical Image Analysis; Biometrics; Autonomous Anomaly Detection in Images; ST: Artificial Intelligence in Aerial and Orbital Imagery; ST: Data Gathering, Curation, and Generation for Computer Vision and Robotics in Precision Agriculture. Part 2: Virtual Reality; Segmentation; Applications; Object Detection and Recognition; Deep Learning; Poster.
| Medienart: |
Buch |
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| Erscheinungsjahr: |
[2023] © 2023 |
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| Erschienen: |
Cham: Springer ; 2023 © 2023 |
| Enthalten in: |
Zur Gesamtaufnahme - Part 1 |
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| Reihe: |
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| Sprache: |
Englisch |
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| Beteiligte Personen: |
Bebis, George [HerausgeberIn] |
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| Congresses: |
ISVC ; 18. ; Stateline, Nev. ; 2023 International Symposium on Visual Computing ; 18 ; Lake Tahoe ; 2023.10.16-18 |
| Links: |
Cover [lizenzpflichtig] |
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| ISBN: |
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| Anmerkungen: |
Literaturangaben |
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| Umfang: |
xlii, 614 Seiten ; Illustrationen, Diagramme |
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| PPN (Katalog-ID): |
1871890888 |
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| 245 | 1 | 0 | |a Advances in visual computing |n Part 1 |c George Bebis, Golnaz Ghiasi, Yi Fang, Andrei Sharf, Yue Dong, Chris Weaver, Zhicheng Leo, Joseph J. LaViola Jr., Luv Kohli, editors |
| 264 | 1 | |a Cham |b Springer |c [2023] | |
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| 490 | 1 | |a Lecture notes in computer science |v 14361 | |
| 500 | |a Literaturangaben | ||
| 505 | 8 | 0 | |a ST: Biomedical Image Analysis Techniques for Cancer Detection,Diagnosis and Management.-Hybrid Region and Pixel-Level Adaptive Loss for Mass Segmentationon Whole Mammography Images.-Deep Learning Based GABA Edited-MRS Signal Reconstruction.-Investigating the Impact ofAttention on Mammogram Classification.-ReFit:A Framework for Refinement of Weakly Supervised SemanticSegmentation using Object Border Fitting for Medical Images.-A Data-centric Approach for Pectoral Muscle Deep LearningSegmentation Enhancements in Mammography Images.-Visualization.-Visualizing Multimodal Time Series at Scale.-Hybrid Tree Visualizations for Analysis of Gerrymandering.-ArcheryVis: A Tool for Analyzing and Visualizing Archery PerformanceData.-Spiro: Order-preserving Visualization inHigh Performance Computing Monitoring.-From Faces To Volumes - Measuring Volumetric Asymmetry in 3DFacial Palsy Scans.-Video Analysis and Event Recognition.-Comparison of Autoencoder Models for Unsupervised RepresentationLearning of Skeleton Sequences.-Local and GlobalContext Reasoning for Spatio-Temporal Action Localization.-Zero-Shot Video Moment Retrieval using BLIP-based Models.-Self-Supervised Representation Learning for FineGrained Human Hand Action Recognition in Industrial Assembly Lines.-ST: Innovations in Computer Vision & Machine Learning for Critical& Civil Infrastructures.-Pretext Tasks in Bridge Defect Segmentation within a ViT-AdapterFramework.-A Few-ShotAttention Recurrent Residual U-Net for Crack Segmentation.-Efficient Resource Provisioning in CriticalInfrastructures based on Multi-Agent Rollout enabled by Deep Q-Learning.-Video-Based Recognition of Aquatic Invasive Species Larvae UsingAttention-LSTM Transformer.-ST: Generalization in Visual Machine Learning.-Latent Space Navigation for Face Privacy: A Case Study on the MNISTDataset.-Domain Generalization for Foreground SegmentationUsing Federated Learning.-ProbabilisticLocal Equivalence Certification for Robustness Evaluation.-Challengesof Depth Estimation for Transparent Objects.-Volumetric Body Composition through Cross-DomainConsistency Training for Unsupervised Domain Adaptation.-Computer Graphics.-Water Animation Using Coupled SPH and Wave Equation.-Neural Rendering into Unity.-Virtual Home Staging: Inverse Rendering and Editing an IndoorPanorama under Natural Illumination.-SwarmCurves: Evolutionary Curve Reconstruction.-Medical Image Analysis.-Brain Cortical Surface Registration with Anatomical Atlas Constraints.-When System Model meets ImagePrior: An Unsupervised Deep Learning Architecture for Accelerated Magnetic Resonance Imaging.-3D Reconstruction from 2DCerebral Angiograms as a Volumetric Denoising Problem.-An Integrated Shape-Texture Descriptor for ModelingWhole-Organism Phenotypes in Drug Screening.-Enhancing Image Reconstruction viaPhase-Constrained Data in an Iterative Process.-Biometrics.-I Got Your Emotion: Emotion Preserving Face De-identification UsingInjection-based Generative Adversarial Networks.-DoppelVer: A Benchmark forFace Verification.-Two-stage Face Detection and Anti-spoofing.-Autonomous Anomaly Detection in Images.-Driver Anomaly Detection Using Skeleton Images.-Driver Anomaly Detection Using Skeleton Images.-Latent Diffusionbased Multi-class Anomaly Detection.-ST: Artificial Intelligence in Aerial and Orbital Imagery.-Investigating the impact of a low-rank tensor-based approach on deforestation imagery.-Str |
| 520 | |a This volume LNCS 14361 and 14362 constitutes the refereed proceedings of the, 16th International Symposium, ISVC 2023, in October 2023, held at Lake Tahoe, NV, USA. The 42 full papers and 13 poster papers were carefully reviewed and selected from 120 submissions. A total of 25 papers were also accepted for oral presentation in special tracks from 34 submissions. The following topical sections followed as: Part 1: ST: Biomedical Image Analysis Techniques for Cancer Detection, Diagnosis and Management; Visualization; Video Analysis and Event Recognition; ST: Innovations in Computer Vision & Machine Learning for Critical & Civil Infrastructures; ST: Generalization in Visual Machine Learning; Computer Graphics; Medical Image Analysis; Biometrics; Autonomous Anomaly Detection in Images; ST: Artificial Intelligence in Aerial and Orbital Imagery; ST: Data Gathering, Curation, and Generation for Computer Vision and Robotics in Precision Agriculture. Part 2: Virtual Reality; Segmentation; Applications; Object Detection and Recognition; Deep Learning; Poster | ||
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| 700 | 1 | |a Ghiasi, Golnaz |e herausgeberin |4 edt | |
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