DOIONLINE 
DOIONLINE Publish In |
International Journal of Advances in Computer Science and Cloud Computing (IJACSCC)-IJACSCC |
 Journal Home Volume Issue |
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Issue |
Volume-9,Issue-1 ( May, 2021 ) | |||||||||
Paper Title |
Review - Convolutional Neural Network for Object Detection | |||||||||
Author Name |
Neha Singh, Sachin Harne, Kusum Sharma | |||||||||
Affilition |
Research Scholar, 2Assistant Professor, Assistant Professor Department of computer Science and Engineering RSR Rungta College of Engineering and Technology, Bhilai, Chhattisgarh, India | |||||||||
Pages |
1-4 | |||||||||
Abstract |
Vision is one of the very essential human senses and it plays the most important role in human perception about surrounding environment. Hence, over thousands of papers have been published on these subjects that propose a variety of computer vision products and services by developing new electronic aids for the blind. This paper aims to introduce a proposed system that restores a central function of the visual system which is the identification of surrounding objects. This method is based on the local features extraction concept. The simulation results using SFIT algorithm and key points matching showed good accuracy for detecting objects. Thus, our contribution is to present the idea of a visual substitution system based on features extractions and matching to recognize and locate objects in images. Keywords - Video Processing; Pattern Recognition; Sift; Keypoints Matching; Visual Substituion System. | |||||||||
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