Deep Convolutional Neural Network for Chicken Diseases Detection

For many years in the society, farmers rely on experts to diagnose and detect chicken diseases. As a result, lose domesticated birds due late diagnoses or lack of reliable experts. With available tools from artificial intelligence machine learning based computer vision image analysis, most common diseases affecting can be identified easily images droppings. In this study, we propose deep solution Convolution Neural Networks (CNN) predict whether faeces belong either three classes. We also leverage use pre-trained models develop for same problem. Based comparison, show that model developed XceptionNet outperforms other all metrics used. The experimental results apparent gain transfer (validation accuracy 9