Various Methods for Object Detection Based on Deep Learning
Arlin Maria Scari1, Neena V V2
1Arlin Maria Scaria,Computer Science and Engineering, Vimaljyothi Engineering College, Kerala, India.
2Neena V V Computer Science and Engineering, Vimaljyothi Engineering College, Kerala, India.
Manuscript received on November 15, 2019. | Revised Manuscript received on November 23, 2019. | Manuscript published on November 30, 2019. | PP: 1642-1646 | Volume-8 Issue-4, November 2019. | Retrieval Number: C4954098319/2019©BEIESP | DOI: 10.35940/ijrte.C4954.118419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The growing technology in the world made-up the deep learning method, which classifies different vehicles from a video. In deep learning technology use different strategies such as RCNN, Fast RCNN, RPN, faster RCNN, YOLO, SSD. All methods offer various accuracy of the identification of the vehicle. The convolutional natural network determining an object detection task exploitation in deep learning. Object detection is very important in AI as well as in videos using pc vision. Through this paper demystifies the important role of deep learning supported by CNN for object detection. And the methodology offers additional correct result. Deep learning techniques shows the development of object detection in various area and the different technics are assessed during this paper.
Keywords: Machine Learning, Deep learning, CNN, RCNN, Fast RCNN, Faster RCNN, YOLO, SSD.
Scope of the Article: Deep Learning.