Acta Scientific Computer Sciences

Research Article Volume 6 Issue 6

Classification and Detection of Melanoma Skin Cancer Using Deep Learning Models

B Hema Kumari, Samudrala Shirisha*, Narmeta Aravind and Guram Akhil

Department of Information Technology, Sreenidhi Institute of Science and Technology, India

*Corresponding Author: Samudrala Shirisha, Department of Information Technology, Sreenidhi Institute of Science and Technology, India.

Received: May 02, 2024; Published: May 08, 2024


Melanoma, which means to "black tumor," is the most risky kind of skin cancer. It has the ability to spread to any region of the body and grows quickly. Melanomas cannot be treated if they are not discovered in their early stages. Thus, early detection is crucial for melanoma treatment. A neural network will be used to identify melanoma cancer. Existing system use Neural Networks and Support Vector Machine to detect melanoma. The accuracy for Neural Network is 60%-75% and by using Support Vector Machine it is 80%. The main disadvantage of this model is no proper image preparation and the training takes a lot of time.

Keywords: Melanoma; Black Tumor; Skin Cancer


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Citation: Samudrala Shirisha., et al. “Classification and Detection of Melanoma Skin Cancer Using Deep Learning Models".Acta Scientific Computer Sciences 6.6 (2024): 10-14.


Copyright: © 2024 Samudrala Shirisha., et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


Acceptance rate35%
Acceptance to publication20-30 days

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