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2019·Sole Developer

Skin Cancer Classification Tool

Deep learning model for dermatologists

Overview

My university final project — a deep learning system to assist dermatologists in classifying skin lesions. The model was trained on the HAM10000 dataset and achieved 92% accuracy on test data.

Built as a web application for easy access in clinical settings.

Key Highlights

  • 92% classification accuracy on HAM10000 dataset
  • Real-time image processing and classification
  • Web interface for clinical use
  • Hamdard University BS CS Final Project

Tech Stack

PythonTensorFlowOpenCVFlaskReact