Object Detection Based on Faster R-CNN
M. Sushma Sri1, B. Rajendra Naik2, K. Jaya Sankar3

1M. Sushma Sri*, Department of ECE, Osmania College of Engineering, Hyderabad, India.
2B. Rajendra Naik, Department of ECE, Osmania College of Engineering, Hyderabad, India.
3K. Jaya Sankar, Department of ECE, Mahatma Gandhi Institute of Technology, Hyderabad, India.

Manuscript received on January 21, 2021. | Revised Manuscript received on February 15, 2021. | Manuscript published on February 28, 2021. | PP: 72-74 | Volume-10 Issue-3, February 2021. | Retrieval Number: 100.1/ijeat.C21860210321 | DOI: 10.35940/ijeat.C2186.0210321
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Abstract: In recent years there is rapid improvement in Object detection in areas of video analysis and image processing applications. Determing a desired object became an important aspect, so that there are many numerous of methods are evolved in Object detection. In this regard as there is rapid development in Deep Learning for its high-level processing, extracting deeper features, reliable and flexible compared to conventional techniques. In this article, the author proposes Object detection with deep neural networks and faster region convolutional neural networks methods for providing a simple algorithm which provides better accuracy and mean average precision. 
Keywords: Object Detection, Deep Learning, Neural Networks, Deep Neural Networks, Convolutional Neural Networks, Region Convolutional Neural Network, Faster Region Convolutional Neural Network
Scope of the Article: Deep Learning