digestive-tract
发表于 2025-3-21 20:09:09
书目名称Deep Learning for Video Understanding影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0284501<br><br> <br><br>书目名称Deep Learning for Video Understanding影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0284501<br><br> <br><br>书目名称Deep Learning for Video Understanding网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0284501<br><br> <br><br>书目名称Deep Learning for Video Understanding网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0284501<br><br> <br><br>书目名称Deep Learning for Video Understanding被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0284501<br><br> <br><br>书目名称Deep Learning for Video Understanding被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0284501<br><br> <br><br>书目名称Deep Learning for Video Understanding年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0284501<br><br> <br><br>书目名称Deep Learning for Video Understanding年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0284501<br><br> <br><br>书目名称Deep Learning for Video Understanding读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0284501<br><br> <br><br>书目名称Deep Learning for Video Understanding读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0284501<br><br> <br><br>
有害
发表于 2025-3-21 21:14:08
Book 2024ng and then introduce how to design better surrogate training tasks to learn video representations. Finally, the book introduces recent self-training pipelines like contrastive learning and masked image/video modeling with transformers. The book provides promising directions, with an aim to promote
SPASM
发表于 2025-3-22 01:57:04
the hotbeds of pretext tasks, which refer to network optimization tasks based on surrogate signals without human supervision, facilitating better performance on video-related downstream tasks. In this chapter, we undertake a comprehensive review of UVL, which begins with a preliminary introduction o
ATP861
发表于 2025-3-22 08:19:14
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头脑冷静
发表于 2025-3-22 09:48:32
2366-1186 n, video captioning, and more.Introduces cutting-edge and st.This book presents deep learning techniques for video understanding. For deep learning basics, the authors cover machine learning pipelines and notations, 2D and 3D Convolutional Neural Networks for spatial and temporal feature learning. F
厌烦
发表于 2025-3-22 15:10:33
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厌烦
发表于 2025-3-22 18:20:38
Angst – Bedingung des Mensch-Seinsirections, e.g., the construction of large-scale video foundation models, the application of large language models (LLMs) in video understanding, etc. By depicting these exciting prospects, we encourage the readers to embark on new endeavors to contribute to the advancement of this field.
left-ventricle
发表于 2025-3-22 23:24:38
Book 2024ions, 2D and 3D Convolutional Neural Networks for spatial and temporal feature learning. For action recognition, the authors introduce classical frameworks for image classification, and then elaborate both image-based and clip-based 2D/3D CNN networks for action recognition. For action detection, th
钢盔
发表于 2025-3-23 02:50:19
,I. Führung der eigenen Person,en successively proposed, promoting this large field to becoming more and more mature. In this chapter, we will briefly introduce the above aspects and travel through the corridors of time to systematically review the chronology of this dynamic field.
transient-pain
发表于 2025-3-23 09:34:22
Fallstudien „Führung von Experten“ons of these backbones. By the end of the chapter, readers will have a solid understanding of the basics of deep learning for video understanding and be well-equipped to explore more advanced topics in this exciting field.