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A Review on Object Detection With Deep Learning

Mody University International Journal of Computing and Engineering Research

Volume 3 Issue 2

Published: 2019
Author(s) Name: Arpit Kumar Sharma, Siddharth Jain and Chirag Goyal | Author(s) Affiliation: Manipal University Jaipur, Jaipur, Rajasthan, India.
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Abstract

Object detection makes a wide placement to make a review on it. Object detection play vital role in getting a proper pictures and video analysis. So due to object detection we will get that proper pictures and videos. Object detection can be done with the deep learning. Deep learning increases the accuracy in object detection. The project has aims to get the perfect object detection with the high level of accuracy. And that accuracy can be achieve by deep learning and show real time performance. We will discuss all the important tool of deep learning. Then we will go through generic object detection and with its types like region proposal generation and classification or regression method. There we will get all methods like R-CNN, fast- R-CNN, faster R-CNN, and tasks which dependent on each other like CNN with SPP. And some more like YOLO and SDD and etc. Each method has their unique property also. We will study about that topic in briefly. On that basis there is challenge of having dependency of object detection on the computer vision system with the help of deep learning. Experiment analysis is also providing to get the different between different types of method of object detection. There is a network which is trained on the most challenging publicly database which is PASCAL VOC, on which object detection is done by annually.

Keywords: Convolutional network, Deep learning, Image, Neural network, Object detection.

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