摘要
Deep learning has achieved substantial success in intelligent video analysis. To practically facilitate deep neural network models in the large-scale video analysis, there are still unprecedented challenges. Deep feature coding, instead of video coding, provides a practical solution for handling the large-scale video surveillance data. To enable interoperability in the context of deep feature coding, standardization is urgent and important. This paper envisions the future deep feature coding standard for the AI-oriented large-scale video management and discusses existing techniques, standards, and possible solutions for these open problems.
| 源语言 | 英语 |
|---|---|
| 文章编号 | 8509149 |
| 页(从-至) | 8-20 |
| 页数 | 13 |
| 期刊 | IEEE Multimedia |
| 卷 | 26 |
| 期 | 2 |
| DOI | |
| 出版状态 | 已出版 - 1 4月 2019 |
| 已对外发布 | 是 |
联合国可持续发展目标
此成果有助于实现下列可持续发展目标:
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可持续发展目标 11 可持续城市和社区
指纹
探究 'AI-Oriented Large-Scale Video Management for Smart City: Technologies, Standards, and beyond' 的科研主题。它们共同构成独一无二的指纹。引用此
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