Underwater Object Detection Based on Image Enhancement and Multi-Branch Structure
作者单位：Yunnan Key Laboratory of Intelligent Control and ApplicationKunming University of Science and Technology Faculty of Mechanical and Electrical EngineeringKunming University of Science and Technology
会议名称：《第43届中国控制会议》
会议日期：1000年
学科分类：08[工学] 080203[工学-机械设计及理论] 0802[工学-机械工程]
关 键 词：Underwater Object Detection Underwater Image Enhancement Attention Mechanisms Color Correction Multibranch Structure
摘 要：Underwater object detection plays an important role for underwater intelligent ***,optical-based underwater images often suffer from color bias,haze-like,small scale object and occlusions,resulting in lower detection accuracy for *** address the above problems,an underwater object detection network based on image enhancement and multibranch structure is ***,a parameter-free color correction attention module is first presented to adjust the color cast of underwater images,providing detection-favorable features to the *** addition,a backbone network and a neck network are constructed based on the attention mechanism and multi-branch structure to improve the detection ability of the network for small and occluded *** decoupled head is further introduced to implement the regression and classification *** qualitative and quantitative experiments show that the proposed method achieves a maximum AP of 53.2% at280 FPS in the UODD dataset,outperforming other mainstream methods.
