The week's pick
Reseach Article
A Review: Object Detection using Deep Learning
| 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
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
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- Ross Girshick, “Fast R-CNN”. International Conference on Computer Vision 27 Sep 2015.
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- 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.
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