PERFORMANCE COMPARISON OF THE RESNET50 AND INCEPTIONV3 DEEP TRANSFER LEARNING MODELS OVER THE BREAST CANCER THERMOS GRAM DATASET

Abstract

This paper simply illustrates a performance comparison of two generally used and efficient deep transfer learning architectures like Resnet50 and InceptionV3. The Resnet50 and IncetionV3 deep transfer learning models are trained and evaluated on the Infrared thermo-gram breast cancer dataset. In this study, both these models are trained as well as fine-tuned for the correct classification of breast cancer from the breast thermo-gram images. The Resnet50 model simply outperforms the InceptionV3 model by achieving an accuracy of more than 85 %.