Open AccessA Review of Convolutional Neural Network Development in Computer Vision
Author(s) -
Hang Zhang
Publication year - 2022
Publication title -
eai endorsed transactions on internet of things
Language(s) - English
Resource type - Journals
ISSN - 2414-1399
DOI - 10.4108/eetiot.v7i28.445
Subject(s) - convolutional neural network , computer science , artificial intelligence , field (mathematics) , segmentation , object detection , layer (electronics) , cellular neural network , deep learning , computer vision , object (grammar) , artificial neural network , chemistry , mathematics , organic chemistry , pure mathematics
Convolutional neural networks have made admirable progress in computer vision. As a fast-growing computer field, CNNs are one of the classical and widely used network structures. The Internet of Things (IoT) has gotten a lot of attention in recent years. This has directly led to the vigorous development of AI technology, such as the intelligent luggage security inspection system developed by the IoT, intelligent fire alarm system, driverless car, drone technology, and other cutting-edge directions. This paper first outlines the structure of CNNs, including the convolutional layer, the downsampling layer, and the fully connected layer, all of which play an important role. Then some different modules of classical networks are described, and these modules are rapidly driving the development of CNNs. And then the current state of CNNs research in image classification, object segmentation, and object detection is discussed.