Domain-adaptive foggy day image target detection method and device

A technology of target detection and domain adaptation, applied in the field of target detection, can solve the problems of poor detection accuracy, insufficient feature map, and high missed detection rate, improve detection frame accuracy and missed detection rate, strengthen domain discrimination ability, save money cost effect
CN112633149AActive Publication Date: 2021-04-09NANJING UNIV OF POSTS & TELECOMM
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Patent Information

Authority / Receiving Office
CN Β· China
Patent Type
Applications(China)
Current Assignee / Owner
NANJING UNIV OF POSTS & TELECOMM
Publication Date
2021-04-09

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Abstract

The invention discloses a domain-adaptive foggy day image target detection method and device, and belongs to the technical field of target detection, and the method comprises the following steps: carrying out preprocessing on an obtained target detection data set; carrying out model multi-scale performance reconstruction on the backbone network; training the reconstructed backbone network by using the preprocessed target detection data set to obtain a target detection model; building a domain classifier for the target detection model; training the target detection model with the domain classifier being built by adopting the foggy day image and the preprocessed target detection data set to obtain a domain-adaptive detection model; and performing target detection on the foggy day image to be detected by using the domain-adaptive detection model. The method and device have the advantages of being high in detection precision, high in real-time performance and applicability, low in omission ratio and the like, and the performance of the detection model in a foggy day scene is improved.
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Description

technical field

[0001] The present invention relates to the technical field of target detection in deep learning and computer vision, in particular to a method and device for domain adaptive fog image target detection. Background technique

[0002] With the development of artificial intelligence-based autonomous driving technology, safety has become an important issue to be solved in intelligent transportation. In recent years, due to the acceleration of industrial development, more and more serious environmental pollution has been caused. Most areas frequently encounter fog, haze, etc. Bad weather is coming. Due to the wide coverage of smog, road visibility is low, which seriously interferes with the detection of traffic elements through cameras in autonomous driving scenarios. Image target detection itself is a research hotspot in the field of deep learning and computer vision. However, in foggy days, the images collected by imaging equipment not only decrease in clarity ...

Claims

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