Image semantic segmentation using deep learning technique

Abstract

With the deepening research on image understanding in many application fields, including auto drive system, unmanned aerial vehicle (UAV) landing point judgment, virtual reality wearable devices, etc., computer vision and machine learning researchers are paying more and more attention to image semantic segmentation (ISS). In this paper, according to the different region generation algorithms, the regional classification image semantic segmentation methods are classified into the candidate region method and the segmentation mask method, according to different learning methods, the image semantic segmentation methods based on super pixels are divided into fully supervised learning method and weakly supervised learning method. The typical algorithms in these various categories are summarized and compared. In addition, this paper also systematically expounds the role of DL technology in the field of ISS, and discusses the main challenges and future development prospects in this field.