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Abstract
This study aims to investigate the application of artificial intelligence (AI) for automatic disease classification in black tiger shrimp (Penaeus monodon). Various common diseases in black tiger shrimp have visual signs that can be recognized through images, suggesting the application of AI techniques in computer vision to build a system capable of predicting common diseases in black tiger shrimp in Vietnam. Experimental results of identifying four common shrimp diseases: black gill, black spot, white spot, and infectious myonecrosis show that the AI model obtained the highest accuracy of 87.58 % with the EfficientNet-B4 model using transfer learning technique. This result suggests the potential of applying AI to disease identification in black tiger shrimp which can shorten the time and cost of disease diagnosis, reducing the damage caused by diseases to shrimp farming.
Keywords: artificial intelligence, computer vision, shrimp disease prediction, smart agriculture