Exploration of Target Detection Technology Under the Background of Deep Learning
Target detection technology occupies an important position in the field of computer vision,and it has made significant progress with the rise of deep learning.From traditional manual detection methods to modern tar-get detection methods,from the early R-CNN series based on candidate regions to the single-stage YOLO series,and then to the DETR series with the addition of the Transformer architecture,target detection technology has been updated with the advancement of science and technology.This paper introduces of mainstream algorithms,compare the advantages and disadvantages of different algorithms in terms of accuracy,speed,resource consumption were compared.Finally,the challenges faced by target detection and future development directions are discussed.
Deep learningTarget detectionOne-stage detectionTwo-stage detection
万方数据
维普
