Underwater Object Detection using Tensorflow
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 det...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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EDP Sciences
2020-01-01
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| Series: | ITM Web of Conferences |
| Online Access: | https://www.itm-conferences.org/articles/itmconf/pdf/2020/02/itmconf_icacc2020_03037.pdf |
| Summary: | 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. |
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| ISSN: | 2271-2097 |