| Issue |
ITM Web Conf.
Volume 32, 2020
International Conference on Automation, Computing and Communication 2020 (ICACC-2020)
|
|
|---|---|---|
| Article Number | 03037 | |
| Number of page(s) | 5 | |
| Section | Computing | |
| DOI | https://doi.org/10.1051/itmconf/20203203037 | |
| Published online | 29 July 2020 | |
Underwater Object Detection using Tensorflow
1 avinashmahavarkar@gmail.com
2 ritika.kadwadkar1525@gmail.com
3 snehamaurya1610@gmail.com
4 smitha.raveendran@rait.ac.in
* e-mail: avinashmahavarkar@gmail.com
** e-mail: ritika.kadwadkar1525@gmail.com
*** e-mail: snehamaurya1610@gmail.com
**** e-mail: smitha.raveendran@rait.ac.in
Object Detection is a popular technology that detects instances within an image. In order to eliminate the barriers in Computer Vision technology due to the dissolution of the BGR(Blue-Green-Red) constituents with the increase in depth, it has been a necessity that the accuracy and efficiency of detecting any object underwater is optimum. In this article, we conduct Underwater Object Detection using Machine Learning through Tensorflow and Image Processing along with Faster R-CNN (Regions with Convolution Neural Network) as an algorithm for implementation. A suitable environment will be created so that Machine Learning algorithm will be used to train different images of the object. Open source Computer Vision has various functions which can be used for the image processing needs when an image is captured.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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