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Video image target monitoring based on RNN-LSTM

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成果类型:
期刊论文
作者:
Liu, Feng;Chen, Zhigang*;Wang, Jie
通讯作者:
Chen, Zhigang
作者机构:
[Chen, Zhigang; Liu, Feng] Cent S Univ, Sch Software, Changsha 410075, Hunan, Peoples R China.
[Liu, Feng] Univ Jinan, Sch Informat Sci & Engn, Jinan, Shandong, Peoples R China.
[Wang, Jie] Hengyang Normal Univ, Coll Comp Sci & Technol, Hengyang, Peoples R China.
通讯机构:
[Chen, Zhigang] C
Cent S Univ, Sch Software, Changsha 410075, Hunan, Peoples R China.
语种:
英文
关键词:
Algorithm design;Deep learning network;Long short-term memory;Recurrent neural network;Target monitoring;Video image
期刊:
Multimedia Tools and Applications
ISSN:
1380-7501
年:
2019
卷:
78
期:
4
页码:
4527-4544
机构署名:
本校为其他机构
院系归属:
计算机科学与技术学院
摘要:
Traditional image object classification and detection algorithms and strategies cannot meet the problem of video image acquisition and processing. Deep learning deliberately simulates the hierarchical structure of human brain, and establishes the mapping from low-level signals to high-level semantics, so as to achieve hierarchical feature representation of data. Deep learning technology has powerful visual information processing ability, which has become the forefront technology and domestic and international research hotspots to deal with this challenge. In order to solve the problem of targe...

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