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Reseach Article

A Review: Object Detection using Deep Learning

by Zinal K. Naik, Monali R. Gandhi
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 180 - Number 29
Year of Publication: 2018
Authors: Zinal K. Naik, Monali R. Gandhi
10.5120/ijca2018916708

Zinal K. Naik, Monali R. Gandhi . A Review: Object Detection using Deep Learning. International Journal of Computer Applications. 180, 29 ( Mar 2018), 46-48. DOI=10.5120/ijca2018916708

@article{ 10.5120/ijca2018916708,
author = { Zinal K. Naik, Monali R. Gandhi },
title = { A Review: Object Detection using Deep Learning },
journal = { International Journal of Computer Applications },
issue_date = { Mar 2018 },
volume = { 180 },
number = { 29 },
month = { Mar },
year = { 2018 },
issn = { 0975-8887 },
pages = { 46-48 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume180/number29/29181-2018916708/ },
doi = { 10.5120/ijca2018916708 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:02:12.165810+05:30
%A Zinal K. Naik
%A Monali R. Gandhi
%T A Review: Object Detection using Deep Learning
%J International Journal of Computer Applications
%@ 0975-8887
%V 180
%N 29
%P 46-48
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Identifying and detecting the different objects in an image is important skill in computer vision. Fast and reliable object detection is significant approach for interacting with one's environment. Human uses a process called as visual attention to quickly decide which location of an image need to be processed in detail and which can be ignored. But for the machine it is difficult task to identify object and exact location of the object in an image. To overcome this difficulty machine learning and deep learning have made great progress with the help of algorithm series based on R-CNN. This algorithm series have given amazing results with the help of some well-known datasets like Image-Net, Pascal voc, coco etc.

References
  1. Xinyi Zhou, Wei Gong, WenLong Fu, Fengtong Du, “Application of Deep learning in Object Detection”: in ICIS, Wuhan, China, pp. 24-26, 2017.
  2. Ross Girshick, Jeff Donahue, Trevor Darrell, Jitendra Malik, “Rich feature hierarchies for accurate object detection and semantic segmentation”: IEEE Conference on Computer Vision and Pattern Recognition, Columbus, USA, June 23-28, 2014, pages: 580-587, 2014.
  3. Wang Zhiqiang, Liu Jun, “A Review of Object Detection Based on Convolutional Neural Network”: Proceedings of the 36th Chinese Control Conference IEEE July 26-28, 2017.
  4. Jawadul H. Bappy, Amit K. Roy Chowdhury, “ CNN based region proposals for efficient object detection”: IEEE International Conference on Image Processing, Phoenix, USA, September 25-28, pages:3658- 3662,2016.
  5. Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun, “Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 37, NO. 9, September 2015.
  6. Ross Girshick, “Fast R-CNN”. International Conference on Computer Vision 27 Sep 2015.
  7. P. N. Druzhkov, v.d. kustikova, “A Survey of Deep Learning Methods and Software Tools for Image Classification and Object Detection.” Pattern Recognition and Image Analysis, 2016, Vol. 26, No. 1, pp. 9–15. © Pleiades Publishing, Ltd., 2016.
  8. Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun, “Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks.” IEEE Transactions on Pattern Analysis and Machine Intelligence, 2016.
Index Terms

Computer Science
Information Sciences

Keywords

Deep learning Neural Network dataset faster Region with Convolutional neural network ROI RPN