Author:
Huang Lanqing,Yao Cheng,Zhang Lingyan,Luo Shijian,Ying Fangtian,Ying Weiqiang
Abstract
AbstractAdvances in computer image recognition have significantly impacted many industries, including healthcare, security and autonomous systems. This paper aims to explore the potential of improving image algorithms to enhance computer image recognition. Specifically, we will focus on regression methods as a means to improve the accuracy and efficiency of identifying images. In this study, we will analyze various regression techniques and their applications in computer image recognition, as well as the resulting performance improvements through detailed examples and data analysis. This paper deals with the problems related to visual image processing in outdoor unstructured environment. Finally, the heterogeneous patterns are converted into the same pattern, and the heterogeneous patterns are extracted from the fusion features of data modes. The simulation results show that the perception ability and recognition ability of outdoor image recognition in complex environment are improved.
Funder
Fundamental Research Funds for the Central Universities
Research Center of Computer Aided Product Innovation Design, Ministry of Education, National Natural Science Foundation of China
National Social Science Foundation of China
Publisher
Springer Science and Business Media LLC