Authors : Augustine Mukumba; Melford Mutandavari

Volume/Issue : Volume 9 - 2024, Issue 7 - July

Google Scholar : https://tinyurl.com/yj9cc3h8

Scribd : https://tinyurl.com/4pajbexw

DOI : https://doi.org/10.38124/ijisrt/IJISRT24JUL463

Abstract : This study focuses on the assessment of a deep learning model for the detection and diagnostics of poultry diseases. The model utilizes a convolutional neural network architecture to automatically analyze images of diseased poultry and accurately classify the type of disease present. The performance of the model is evaluated by comparing its predictions with expert- annotated data. The results show that the deep learning model achieves high accuracy in detecting common poultry diseases, outperforming traditional methods. This novel approach has the potential to revolutionize the field of poultry healthcare by providing fast and accurate diagnostics, leading to improved disease management and welfare for poultry populations.

Keywords : Convolutional Neural Networks, Poultry Disease, Deep Learning, Detection, Diagnostics and Classification.

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