目标检测
计算机科学
计算机视觉
人工智能
对象类检测
对象(语法)
行人检测
Viola–Jones对象检测框架
领域(数学)
特征提取
模式识别(心理学)
行人
人脸检测
工程类
数学
纯数学
运输工程
面部识别系统
作者
Abhinandan Tripathi,Manish Gupta,Chaynika Srivastava,Pallavi Dixit,Shrawan Kumar Pandey
标识
DOI:10.1109/ic3i56241.2022.10073281
摘要
In recent years, object detection is becoming very popular field in computer vision developments. Object detection has many applications viz. vehicle detection, pedestrian detection, blood cell counting etc. Various studies have been conducted in order to improve object detecting accuracy and speed. The latest technique is You Only Look Once object detection. It is state-of-the-art detection technique and considered as a regression problem. YOLO has the ability to predict various objects present in an image in a single run. This paper presents a survey of various detections based on YOLO which aims to improve the accuracy of existing system. This paper presents various modifications done on basic YOLO method and shows their analysis.
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