Image Data for Beef and Lamb Slices Authentication

Existing meat authentication methods usually relay on special devices, and thus are limited to professional use only. Based on deep learning technique, we present a customer-manipulated method for hotpot lamb and beef slices authentication.

This method takes a single image as input, and obtain authentication result rapidly. We build a lightweight (thus high-efficiency) convolutional neural network architecture called MTx-Net for this task. For training and testing the neural network, we collected 77956 meat images using over 225kg of meat.