Real-Time Object Detection with Yolo
Geethapriya. S1, N. Duraimurugan2, S.P. Chokkalingam3
1Geethapriya S, ME. Student, Department of CSE, Rajalakshmi Engineering College, Chennai, Tamil Nadu, India.
2N.Duraimurugan Assistant Professor, Department of CSE, Rajalakshmi Engineering College, Chennai (Tamil Nadu), India.
3S.P. Chokkalingam, Professor, Department of CSE, Saveetha School of Engineering, Chennai (Tamil Nadu), India.
Manuscript received on 29 May 2019 | Revised Manuscript received on 11 June 2019 | Manuscript Published on 22 June 2019 | PP: 578-581 | Volume-8 Issue-3S, February 2019 | Retrieval Number: C11240283S19/19©BEIESP
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Abstract: The Objective is to detect of objects using You Only Look Once (YOLO) approach. This method has several advantages as compared to other object detection algorithms. In other algorithms like Convolutional Neural Network, Fast-Convolutional Neural Network the algorithm will not look at the image completely but in YOLO the algorithm looks the image completely by predicting the bounding boxes using convolutional network and the class probabilities for these boxes and detects the image faster as compared to other algorithms.
Keywords: Convolutional Neural Network, Fast-Convolutional Neural Network, Bounding Boxes, YOLO.
Scope of the Article: Multimedia and Real-Time Communication