Extraction of Ship Images using Deep Learning 
Pavithra G.K.1, Shridevi. S2
1Pavithra G.K*, Vellore Institute of Technology, Chennai, India.
2Shridevi.S, Vellore Institute of Technology, Chennai, India.
Manuscript received on May 29, 2020. | Revised Manuscript received on June 22, 2020. | Manuscript published on June 30, 2020. | PP: 635-638 | Volume-9 Issue-5, June 2020. | Retrieval Number: E9682069520/2020©BEIESP | DOI: 10.35940/ijeat.E9682.069520
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Ship Extraction is very important in the marine industry. Extraction of ships is helpful to the fishers to find the other ships nearly around the particular area. Still today the fishers are to find the ships using some traditional methods. But now it became difficult due to environmental changes. So, by using the deep learning techniques like the CNN algorithm the ship extraction can be identified effectively. Generally, the ships are identified as narrow bow and parallel hull edge, etc. Here, the Existing system they have used the Tensor flow, to see the performance of the datasets, using Recall and precision. In the proposed system, we are using CNN deep learning techniques to identify the ships. By finding the ships with the techniques, the time will be saved and the productivity can be increased. The features of the ship image are taken and trained using the neural network algorithm and then the prediction is done by testing the images.
Keywords: Ship Extraction, Data augmentation, ResNet, CNN.