USE OF UNet++ ALGORITHM IN DETERMINATION OF EAR DISEASES

The proposed method applies the ResNet152 layer structure to the encoders in the UNet++ model to detect the location of the TM and affected area with high accuracy. Furthermore, the TM and affected regions can be segmented better than when using the previously proposed UNet and UNet++ models. To the best of our knowledge, this study is the first to use a UNet++-based segmentation model to segment TM areas in endoscopic images of the TM and evaluate its performance. The experiments revealed that ResNet152 UNet++ outperforms conventional methods in terms of segmentation of the TM and affected areas