Target Detection Algorithm Based On Human Judge Mechanism  

作　　者：SHI Jichao WANG Ziheng ZHAO Xianchao ZHANG Zhinan 石继超;王子恒;赵现朝;张执南(School of Mechanical Engineering,Shanghai Jiao Tong University,Shanghai,200240,China;Whiting School of Engineering,Johns Hopkins University,Baltimore,MD,21218,USA)

机构地区：[1]School of Mechanical Engineering,Shanghai Jiao Tong University,Shanghai,200240,China [2]Whiting School of Engineering,Johns Hopkins University,Baltimore,MD,21218,USA

出　　处：《Journal of Shanghai Jiaotong university(Science)》2022年第5期660-670,共11页上海交通大学学报（英文版）

基　　金：the Humanities and Social Science Research Special Tasks of the Ministry of Education Funded Project(No.17JDGC008)。

摘　　要：A D-G-YOLOV3 algorithm was proposed to identify and judge recyclables,which introduced a dense feature network to replace the feature pyramid network.The network closely connects and fits the feature maps and simulates human judgment mechanism.A three-stage judgment is made for judgment objects with lower confidence.Based on the judgment of the original image,the second-stage judgment is carried out after the channel contrast is increased.Finally,sampling is performed on the region of interest where the second-stage confidence score wins for the third stage of judgment,and then judgment result is sent to the gated recurrent unit network for final inference.The result shows that through experiments on the same recyclables data set,the algorithm reduces the missed detection rate by 15.54%,and the false detection rate by 0.97%,while improves the accuracy rate by 16.51%.

关 键 词：target detection dense feature network human judge mechanism RECYCLABLE 

分 类 号：V19[航空宇航科学与技术—人机与环境工程] TP241[自动化与计算机技术—检测技术与自动化装置]