Data Science and Intelligent Computing Techniques
Recognition of Skin Cancer, an Approach of Deep Learning
Authors: Nikita Gajbhiye and Sujata Kadu
Publishing Date: 05-11-2023
ISBN: 978-81-955020-2-8
Abstract
Predicting a disease with precision or accuracy based on visual diagnosis of cell type is a time-consuming process, certainly when several characteristics are involved. If we collect data about useless pores and skin that isn't always clear to the naked eye in a well-timed manner, we are able to prevent sickness from spreading to different elements of the frame. One of the most important difficulties in the medical field is that doctors are unable to hit upon inflamed elements of the skin that are not viewable to the unaided eye, so that they only perform at the sensitive infected part of the pores and skin, which may additionally result in a primary hassle within the future, inclusive of ailment or any dangerous sickness. The association between the skin illness image and several types of neural networks is formed in this skin disease classification system. The system receives the medical images and enhances the image attributes using various image processing algorithms. For the detection of dead skin, useful records may be gathered from those scientific photos and surpassed to the class system for analysing and testing the use of CNN photograph processing.
Keywords
Medical images, the detection of dead skin, analyzing and testing
Cite as
Nikita Gajbhiye and Sujata Kadu, "Recognition of Skin Cancer, an Approach of Deep Learning", In: Satyasai Jagannath Nanda and Rajendra Prasad Yadav (eds), Data Science and Intelligent Computing Techniques, SCRS, India, 2023, pp. 583-591. https://doi.org/10.56155/978-81-955020-2-8-53