2024 Vol.7 Feb.N01

• Title: Multi-target detection algorithm for low illumination scenes based on dilated convolutional attention neural network
• Name: YanDan Xu
• Company: Huzhou Vocational & Technical College,HuZhou 313099 China
• Abstract:

  Current conventional multi-target detection algorithms in low illumination scenes mainly preprocess the scene images, remove the noise, and build out the detection module, which leads to poor detection results due to the lack of feature enhancement processing of the scene images. In this regard, a multi-target detection algorithm for low illumination scenes based on dilated convolutional attention neural network is proposed. Firstly, the LOL paired dataset with low contrast is adopted as the training set and test set of the image enhancement part to build the image enhancement module. Then the extracted image features are processed by multi-scale fusion, and finally the multi-target detection framework is built. In the experiments, the detection effect of the proposed method is examined. It is clear from the experimental analysis that when the proposed method is used for multi-target detection, the detection accuracy is high, and it has a more ideal detection effect.

  
  

• Keyword: low illumination; scene detection; multi-objective; detection algorithms ;
• DOI: 10.12250/jpciams2024090208
• Citation form: YanDan Xu.Multi-target detection algorithm for low illumination scenes based on dilated convolutional attention neural network [J]. Computer Informatization and Mechanical System,2024,Vol.7,pp.33-37

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