Effect Verification of Transfer Learning on Fatty Liver Classification with Chicken Liver Image based on Convolutional Neural Networks

Abstract

Fat content is an important index of the added value of meat and livestock by-products. In this study, CNN was used to classify the normal liver and fatty liver to identify the morphology of chicken liver. To recognize the appearance of chicken liver, the feature extraction method, and the trained deep learning model vgg16 were used for transfer learning. The validity of vgg16 is verified by comparing it with the baseline model without transfer learning.