A Review on Object Detection With Deep Learning
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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