Detection of wagyu beef sources with image classification using convolutional neural network

Abstract

Wagyu beef originated in Japan. However, there are many types of Wagyu beef in the market around the globe. Primary sources include Australia, USA, Canada and the United Kingdom. The authentic Japanese Wagyu is well known for its intense marbling, juicy rich flavor and tenderness. Observing that there are differences in flavor, texture, and quality between distinct sources of Wagyu. This research presents an AI-based approach to identify Wagyu beef sources with image classification. The input images were collected from reliable sources on the internet and augmented with DCGAN. Deep neural networks, CNN, was constructed to detect the marbled fat patterns of two sources, Japanese Wagyu and Australian Wagyu. The prediction of Wagyu sources achieved high accuracy of 94.2%. Further experiment was conducted for multi-classification with the additional source of the US wagyu. The object detection model was trained using Region-based CNN, R-CNN, providing the prediction accuracy of 79.8%. The learning models of Convolutional Neural Networks were found to be promising methods for the rapid characterization of the unique patterns of marbled fat layers. These classifiers would benefit the customers for buying Wagyu beef at reasonable prices.