An Improved Algorithm for Target Detection in Low Light Conditions. Issue 1 (1st February 2022)

• Record Type: Journal Article
• Authors: Yin, Dan; Tang, Wengsheng; Chen, Peng; Yang, Bo
• Is Part Of: Journal of physics. Volume 2203:Issue 1(2022)
• Publication Date: 2022-02-01
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/2203/1/012045
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: The accuracy of pig target detection is not ideal due to insufficient light in a real pig farm environment. An improved enhanced network helps to increase the accuracy for pig target detection. The ResNet-Attention-RetinexNet algorithm (RA-RetinexNet) is proposed to solve the problems that YOLO V4 has low accuracy in pig image detection under low light and Mosaic data enhancement method cannot improve the brightness of low light image. In this model, we build residual connection and add attention mechanism, decreasing data loss of RetinexNet and enhancing the brightness information of images. The experimental results show that the model achieves better performance for pig target detection under low light.