Recurrent self-optimizing proposals for weakly supervised object detection

Ming Zhang; Bing Zeng

doi:10.1007/s00521-022-07818-w

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Recurrent self-optimizing proposals for weakly supervised object detection

Ming Zhang Bing Zeng

Year: 2022 Journal: Neural Computing and Applications Vol: 35 (1)Pages: 757-771 Publisher: Springer Science+Business Media

DOI: 10.1007/s00521-022-07818-w

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Keywords:

Computer science Object (grammar) Focus (optics) Process (computing) Object detection Artificial intelligence Noise (video) Transformation (genetics) Machine learning Quality (philosophy) Filter (signal processing) Supervised learning Image (mathematics) Data mining Pattern recognition (psychology) Computer vision Artificial neural network

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Video Surveillance and Tracking Methods

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Advanced Image and Video Retrieval Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Advanced Neural Network Applications

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Recurrent self-optimizing proposals for weakly supervised object detection

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