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Chandragandhi, S.
- Novel Deep Intelligence Method for the Detection of Environmental Pollutants Using SAR Images on Oceans
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1 Department of Computer Science and Engineering, Veltech High Tech Dr. Rangarajan Dr. Sakunthala Engineering College, IN
2 Department of Computer Science and Engineering, Tagore Engineering College, Chennai, IN
3 Department of Computer Science and Engineering, Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology, IN
4 Department of Artificial Intelligence and Data Science, Karpagam Institute of Technology, IN
1 Department of Computer Science and Engineering, Veltech High Tech Dr. Rangarajan Dr. Sakunthala Engineering College, IN
2 Department of Computer Science and Engineering, Tagore Engineering College, Chennai, IN
3 Department of Computer Science and Engineering, Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology, IN
4 Department of Artificial Intelligence and Data Science, Karpagam Institute of Technology, IN
Source
ICTACT Journal on Image and Video Processing, Vol 13, No 4 (2023), Pagination: 2953-2958Abstract
The decline of marine ecosystems poses a substantial threat to the viability of local economies that are reliant on marine life for their continued survival. Artificial intelligence (AI) and machine learning (ML) are two of the several developing technologies that have the ability to address environmental challenges. In particular, ML may be used to better analyse the oceans, keep track of shipping, maintain track of debris in the ocean, unregulated and unreported (IUU) fishing, ocean mining, reduce coral bleaching, and stop the spread of marine diseases. In this paper, we examine the rising prospects and concerns related with the application of AI in the maritime environment, as well as their potential scalability for larger results, using some use-cases to illustrate our points. The results that were obtained when the model prediction was applied to random images are evidence that the model that was suggested provides better outcomes with fewer data points.Keywords
SAR, Ocean, Pollution, Deep Intelligence, Detection.References
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