Computer Vision Systems

13th International Conference, ICVS 2021, Virtual Event, September 22-24, 2021, Proceedings

Häftad, Engelska, 2021

Av Markus Vincze, Timothy Patten, Henrik I Christensen, Lazaros Nalpantidis, Ming Liu

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This book constitutes the refereed proceedings of the 13th International Conference on Computer Vision Systems, ICVS 2021, held in September 2021. Due to COVID-19 pandemic the conference was held virtually.The 20 papers presented were carefully reviewed and selected from 29 submissions. cover a broad spectrum of issues falling under the wider scope of computer vision in real-world applications, including among others, vision systems for robotics, autonomous vehicles, agriculture and medicine. In this volume, the papers are organized into the sections: attention systems; classification and detection; semantic interpretation; video and motion analysis; computer vision systems in agriculture.

Produktinformation

Utgivningsdatum2021-09-19
Mått155 x 235 x 143 mm
Vikt418 g
FormatHäftad
SpråkEngelska
SerieTheoretical Computer Science and General Issues
Antal sidor259
FörlagSpringer Nature Switzerland AG
ISBN9783030871550

Tillhör följande kategorier

Systemvetenskap och AI inom Data och it
Nätverk och kommunikation inom Data och it

Attention Systems.- Thermal Image Super-Resolution Using Second-Order Channel Attention with Varying Receptive Fields.- MARL: Multimodal Attentional Representation Learning for Disease Prediction.- Object Localization with Attribute Preference based on Top-Down Attention.- See the silence: improving visual-only voice activity detection by optical flow and RGB fusion.- Classification and Detection.- Score to Learn: a Comparative Analysis of Scoring Functions for Active Learning in Robotics.- Enhancing the performance of image classification through features automatically learned from depth-maps.- Object Detection on TPU Accelerated Embedded Devices.- Tackling Inter-Class Similarity and Intra-Class Variance for Microscopic Image-based Classification.- Semantic Interpretation.- Measuring the Sim2Real gap in 3D Object classification for different 3D data representation.- Spatially-Constrained Semantic Segmentation with Topological Μaps and Visual Εmbeddings.- Knowledge-enabled generation of semantically annotated image sequences of manipulation activities from VR demonstrations.- Make It Easier: An Empirical Simplification of a Deep 3D Segmentation Network for Human Body Parts.- Video and Motion Analysis.- Video Popularity Prediction through Fusing Early Viewership with Video Content.- Action Prediction during Human-Object Interaction based on DTW and Early Fusion of Human and Object Representations.- GridTrack: Detection and Tracking of Multiple Objects in Dynamic Occupancy Grids.- An Efficient Video Desnowing and Deraining Method with a Novel Variant Dataset.- Computer Vision Systems in Agriculture.- Robust Counting of Soft Fruit through Occlusions with Re-identification.- Non-destructive Soft Fruit Mass and Volume Estimation for Phenotyping in Horticulture.- Learning Image-based Contaminant Detection in Wool Fleece from Noisy Annotations.- Active Learning for Crop-Weed Discrimination by Image Classification from Convolutional Neural Network’s Feature Pyramid Levels.