Object Helps U-Net Based Change Detectors

作     者：Lan Yan Qiang Li Kenli Li Lan Yan;Qiang Li;Kenli Li

作者机构：College of Computer Science and Electronic EngineeringHunan UniversityChangsha 410082China State Key Laboratory for Management and Control of Complex SystemsInstitute of AutomationChinese Academy of SciencesBeijing 100190China 

出 版 物：《IEEE/CAA Journal of Automatica Sinica》 (自动化学报（英文版）)

年 卷 期：2024年第11卷第2期

页      面：548-550页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 081104[工学-模式识别与智能系统] 080203[工学-机械设计及理论] 0802[工学-机械工程] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported in part by the National Natural Science Foundation of China (62302161, 62303361) the Postdoctoral Innovation Talent Support Program(BX20230114) 

主　　题：Net computer networks 

摘      要：Dear Editor,This letter focuses on leveraging the object information in images to improve the performance of the U-Net based change *** detection is fundamental to many computer vision *** existing solutions based on deep neural networks are able to achieve impressive results.