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Skin Disease Detection system built on an application comprising of a front-end and a back-end that uses Machine learning, Deep learning, and image processing techniques to identify skin diseases.

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CutiCare

A Flutter project that allows the user to diagnose the five most prevalent skin diseases.

Overview

The major goal of the project was to develop a cross-platform skin disease detection mobile application that could identify up to three prevalent skin diseases using deep learning. Our team was able to cover 5 skin illnesses using the DermNet dataset along with the transfer learning approach with ResNet-50 model, achieving a 60 percent accuracy. TensorFlow, a Python package, was used along with several other machine learning libraries, such as NumPy, Keras, and Pandas, which helped in the model's construction.

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Skin Disease Detection system built on an application comprising of a front-end and a back-end that uses Machine learning, Deep learning, and image processing techniques to identify skin diseases.

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