A Smartphone-Based Skin Disease Classification Using MobileNet CNN
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The MobileNet model was used by applying transfer learning on the 7 skin diseases to create a skin disease classification system on Android application. The proponents gathered a total of 3,406 images and it is considered as imbalanced dataset because of the unequal number of images on its classes. Using different sampling method and preprocessing of input data was explored to further improved the accuracy of the MobileNet. Using under-sampling method and the default preprocessing of input data achieved an 84.28 using imbalanced dataset and default preprocessing of input data achieved a 93.6 model attained a 91.8 data augmentation on preprocessing the input data provide a 94.4 this model was deployed on the developed Android application.
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