计算机科学
目标检测
卷积神经网络
人工智能
对象类检测
过程(计算)
对象(语法)
机器学习
计算机视觉
特征提取
模式识别(心理学)
人脸检测
面部识别系统
操作系统
作者
Sonia Setia,Akanksha Shukla,A. Arockia Bazil Raj,Ajayver Singh Rathore
标识
DOI:10.1109/icoei56765.2023.10125764
摘要
Nowadays., object detection has become very crucial in the area of computer vision. Many day-to-day activities require the use of technology that can help in vigilance such as traffic rules violations., road safety., etc. The detection techniques work on the images or videos and act as a model that provide the required area of interest from that input media. To solve these existing problems., different algorithms are available to perform object detection. This study focuses on reviewing the available algorithms to assist in the detection of object based on time and accuracy. The end result will help to identify the best available algorithm that can achieve faster object detection. The algorithms taken for the review process are CNN (Convolutional Neural Networks)., RCNN., Fast CNN., Faster RCNN., Single shot., YOLO (You Only Look Once).
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