The poultry sector is facing significant challenges due to the spread of diseases such as Coccidiosis, Salmonella, and Newcastle, which can have a significant impact on production.Traditional farming practices and a lack of reliable information and proper methods of farming have contributed to the spread of these diseases.Poultry farmers rely on experts to diagnose and detect diseases, but access to experts is limited due to the shortage of extension officers.Artificial intelligence and machine learning tools can help semi -automate the diagnostics process for the most common diseases in chickens.This study proposes a solution for predicting diseases in chickens using chicken fecal images, and deep Convolutional Neural Networks (CNN).The proposed CNN model can classify healthy and diseased chicken fecal images as Coccidiosis, Salmonella, Newcastle, or healthy.Also, it gives some information about it.
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M. N. Savitha (2024) studied this question.
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