Skin Lesion Detection and Classification Using Transfer Learning

Many people each year die from skin cancer, and this statistic is rising steadily each year. Survival rates are high if detected early. Dermatologists have been trying different methods to aid in the detection skin cancer . Lack of experience and knowledge causes incorrect detection. The purpos

Project Title

Skin Lesion Detection and Classification Using Transfer Learning

Project Area of Specialization

Computer Science

Project Summary

Many people each year die from skin cancer, and this statistic is rising steadily each year. Survival rates are high if detected early. Dermatologists have been trying different methods to aid in the detection skin cancer . Lack of experience and knowledge causes incorrect detection. The purpose of this project is to present an automatic skin lesions classification system with higher classification rate using the theory of transfer learning and the pre-trained deep neural network.

Project Objectives

The main objectives of this research work are

• To study the latest approaches that support skin cancer detection at an early stage.
• To develop the framework that will automatically detect skin cancer detection with help of computer vision technique.
• To improve the accuracy of skin lesion detection.

Project Implementation Method

Experimental setup for proposed research includes the following. PC Core i5. 32/64-bit operating system. Microsoft Windows 7/8. MATLAB 2018 a/b.

Benefits of the Project

The proposed method will improves the accuracy of automatic skin lesion detection.

Technical Details of Final Deliverable

This research will assist physician in classifying skin lesion detection.

Final Deliverable of the Project

Hardware System

Core Industry

Health

Other Industries

Medical

Core Technology

Others

Other Technologies

Sustainable Development Goals

Good Health and Well-Being for People

Required Resources

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