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Titlebook: Advances in Visual Computing; 14th International S George Bebis,Richard Boyle,Panpan Xu Conference proceedings 2019 Springer Nature Switzer

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發(fā)表于 2025-3-21 18:28:28 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Advances in Visual Computing
期刊簡(jiǎn)稱14th International S
影響因子2023George Bebis,Richard Boyle,Panpan Xu
視頻videohttp://file.papertrans.cn/151/150104/150104.mp4
學(xué)科分類Lecture Notes in Computer Science
圖書(shū)封面Titlebook: Advances in Visual Computing; 14th International S George Bebis,Richard Boyle,Panpan Xu Conference proceedings 2019 Springer Nature Switzer
影響因子.This book constitutes the refereed proceedings of the 14th International Symposium on Visual Computing, ISVC 2019, held in Lake Tahoe, NV, USA in October 2019...The 100 papers presented in this double volume were carefully reviewed and selected from 163 submissions. The papers are organized into the following topical sections: Deep Learning I; Computer Graphics I; Segmentation/Recognition; Video Analysis and Event Recognition; Visualization; ST: Computational Vision, AI and Mathematical methods for Biomedical and Biological Image Analysis; Biometrics; Virtual Reality I; Applications I; ST: Vision for Remote Sensing and Infrastructure Inspection; Computer Graphics II; Applications II; Deep Learning II; Virtual Reality II; Object Recognition/Detection/Categorization; and Poster. .
Pindex Conference proceedings 2019
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DeepGRU: Deep Gesture Recognition Utility streamlined and device-agnostic. DeepGRU, which uses only raw skeleton, pose or vector data is quickly understood, implemented, and trained, and yet achieves state-of-the-art results on challenging datasets. At the heart of our method lies a set of stacked gated recurrent units (GRU), two fully-con
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DomainSiam: Domain-Aware Siamese Network for Visual Object Trackingrks. However, Siamese trackers do not fully utilize semantic and objectness information from pre-trained networks that have been trained on image classification task. Furthermore, the pre-trained Siamese architecture is sparsely activated by the category label, which leads to unnecessary calculation
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Reconstruction Error Aware Pruning for Accelerating Neural Networksccelerating the inference. REAP is an extension of one of the state-of-the-art channel pruning methods. Our method takes 3 steps, (1) evaluating the importance of each channel based on the reconstruction error of the outputs in each convolutional layer, (2) pruning less important channels, (3) updat
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Bioinspired Simulation of Knotting Hagfishfor a wide variety of purposes, such as feeding and manipulation. Clearly of interest to biologists, this knotting behavior is also relevant to other fields, such as bioinspired soft robotics. However, this knot-sliding behavior has been challenging to model and has not been simulated on a computer.
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Interactive 3D Visualization for Monitoring and Analysis of Geographical Traffic Data of Various Domrch effort goes into visualization techniques of various kinds of geography-bound traffic data. Unfortunately, such techniques are very domain-specific and often lack useful features. We propose an interactive visualization system for monitoring and analyzing traffic data on a 3D globe. Our system i
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