An Overview on Machine Learning Techniques for Identification of Diseases in Aquaculture
Rakesh GR, C. Raghavendra, S Rohit, P Shetty, Shreeshma Hegde
Abstract
Fish diseases are the ones that thwart the production of small and large scale fish farming sectors. Although there are many physical methodologies based on manual observation involved in finding a solution, they are not 100 percent accurate. As technologies advance in the current scenario, it is the only solution for early detection of diseases with high accuracy, which is necessary and may prevent loss. Since fish are sensitive creatures, early detection and diagnosis is essential. This study offers an overview of diseases in fish and the many approaches used in disease detection. It also includes a comparison between the different techniques involved. The final approach is to identify and detect diseases efficiently, which will be a boon to small and large aquaculture sector in the future.