Identification of Cattle's Breed Type by Processing Image Using Deep Learning Models

Accurately identifying cattle breeds is crucial for effective livestock management and breeding. This research work uses advanced computer techniques to automatically recognize cattle breeds from images. It was used with Convolutional Neural Networks (CNNs), which are good at detecting specific details in images to distinguish one breed from another. Before predicting, images are prepared and enhanced to ensure accurate results. The research work tests CNN models like DenseNet201, MobileNetV2, and Xception to determine which performs bettter. It measured performance using metrics like precision, recall, and F1 score. This automated approach provides farmers and breeders with a reliable tool to identify breeds and improve management. CNN technology helps modernize traditional farming methods, supporting sustainable livestock care. The study aims to find the most accurate CNN model for predicting cattle breeds, emphasizing the benefits of automated systems in maintaining breed purity, genetic diversity, and overall livestock health.