YOLO 시리즈(V1에서 V11까지)와 응용 애플리케이션 분석 비교
Comparative Analysis of YOLO Series (from V1 to V11) and Their Application in Computer Vision

초록

Deep Learning has emerged as multi-domain innovation aimed the popularity of various Machine Learning techniques, and YOLO makes it possible for widely using in deep learning for object detection tasks. In this paper, we present a analysis of YOLO series (original scheme to version 11), undertaking a comprehensive analysis of YOLO’s performance and synthesizes existing researches. We start by describing the architecture and contribution of YOLO families, discussing the major changes in network architecture, and training tricks for each model. Then, se summarize the necessary lessons form YOLO’s development and provide a perspective on its highlighting research directions to enhance object detection.

키워드

Object DetectionDeep LearningComputer VisionYou Only Look Once(YOLO)YOLO Comparison
제목
YOLO 시리즈(V1에서 V11까지)와 응용 애플리케이션 분석 비교
제목 (타언어)
Comparative Analysis of YOLO Series (from V1 to V11) and Their Application in Computer Vision
저자
이용환김흥준
발행일
2024-12
저널명
반도체디스플레이기술학회지
23
4
페이지
190 ~ 198