Open AccessAn Analysis on Multi – Image Classification Techniques
Author(s) -
Ms. Thikshaya M*,
Mr.Vishal C
Publication year - 2020
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.i6887.079920
Subject(s) - inpainting , overfitting , artificial intelligence , convolutional neural network , computer science , image (mathematics) , pattern recognition (psychology) , contextual image classification , random forest , process (computing) , artificial neural network , computer vision , operating system
Image classification is a process where images are classified based on its visual content. It came into existence to reduce the gap between computer vision and human vision. To classify the images, humans involve lot of efforts and it is time consuming, in order to overcome this, technique such as convolutional neural network and random forest is being used. Convolutional neural network is a class of deep neural network and it is most commonly used for analyzing the images. Random forest is classification algorithms which consist of many independent decision trees. Auto encoding technique is being used to denoise the image. Image inpainting technique is adopted to come up with a complete image which contains missing parts. Image inpainting technique is a process to overcome overfitting.