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International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
← Back to VOLUME 11, ISSUE 6, JUNE 2022

OBJECT DETECTION USING CONVOLUTIONAL NEURAL NETWORK

K. Sowmya Sri, A. Ajith Rao, T. Ranveer Singh and Mrs. A.V Lakshmi Prasuna

DOI: 10.17148/IJARCCE.2022.116115

Abstract: Object detection and recognition systems have gained significant interest of researchers due to vast advancement in the field of computer vision technology. Although there are number of object recognition systems implemented in past researches, there still remains a constant demand for new, better and accurate recognition systems. Current detection systems make use of classifiers to perform detection. We are implementing a machine learning model which can detect objects using the concept of Convolutional neural networks (CNNs). This enables us to detect objects with very high accuracy.

Keywords: Neural Network, Opencv, YOLO, Non-Max Suppression

How to Cite:

[1] K. Sowmya Sri, A. Ajith Rao, T. Ranveer Singh and Mrs. A.V Lakshmi Prasuna, “OBJECT DETECTION USING CONVOLUTIONAL NEURAL NETWORK,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2022.116115