Browsing by Author "Damilare Andrew Omideyi, Rafiu Mope Isiaka, Ronke Seyi Babatunde"

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    An enhanced image based mobile deep learning model for identification of Newcastle poultry disease
    (Published by School of Mathematics and Computing, Kampala International University, 2024-06-11) Damilare Andrew Omideyi, Rafiu Mope Isiaka, Ronke Seyi Babatunde
    An enhanced mobile deep learning model based on images is presented in this paper to identify Newcastle poultry disease. A dataset of manually annotated and labeled images of the disease was utilized to pre-train an image-based Convolutional Neural Network (CNN). An Android smartphone app was developed to communicate with the model. A local server was integrated with the generated model to do image classification. A mobile application was developed and made available, enabling users to upload a fecal photograph to a website housed on the streamlet server and obtain the model's processed findings. The user regains control over their health status. The model achieved an accuracy of 95% on the test set and was able to correctly identify specific instances of Newcastle poultry disease. The paper discusses the advantages of a mobile-based approach in comparison to traditional methods of identification and proposes the model as an effective low-cost solution for farmers and researchers.