Open AccessAn Analysis on Object Recognition Using Convolutional Neural Networks
Publication year - 2021
Publication title -
international journal of advanced trends in computer science and engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3091
DOI - 10.30534/ijatcse/2021/611032021
Subject(s) - computer science , convolutional neural network , paraphernalia , object (grammar) , artificial intelligence , deep learning , transfer of learning , object detection , cognitive neuroscience of visual object recognition , globe , architecture , machine learning , computer vision , pattern recognition (psychology) , archaeology , history , medicine , art , ophthalmology , visual arts
The global development and progress in scientific paraphernalia and technology is the fundamental reason for the rapid increasein the data volume. Several significant techniques have been introducedfor image processing and object detection owing to this advancement. The promising features and transfer learning of ConvolutionalNeural Network (CNN) havegained much attention around the globe by researchers as well as computer vision society, as a result of which, several remarkable breakthroughs were achieved. This paper comprehensively reviews the data classification, history as well as architecture of CNN and well-known techniques bytheir boons and absurdities. Finally, a discussion for implementation of CNN over object detection for effectual results based on their critical analysis and performances is presented