
A Review of Image Classification Algorithms in IoT
Author(s) -
Xiaopeng Zheng,
Rayan S Cloutier
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.v7i28.562
Subject(s) - convolutional neural network , computer science , artificial intelligence , contextual image classification , deep learning , image (mathematics) , machine learning , pattern recognition (psychology) , algorithm
With the advent of big data era and the enhancement of computing power, Deep Learning has swept the world. Based on Convolutional Neural Network (CNN) image classification technique broke the restriction of classical image classification methods, becoming the dominant algorithm of image classification. How to use CNN for image classification has turned into a hot spot. After systematically studying convolutional neural network and in-depth research of the application of CNN in computer vision, this research briefly introduces the mainstream structural models, strengths and shortcomings, time/space complexity, challenges that may be suffered during model training and associated solutions for image classification. This research also compares and analyzes the differences between different methods and their performance on commonly used data sets. Finally, the shortcomings of Deep Learning methods in image classification and possible future research directions are discussed.