Shaikh, Adiba and Shaikh, Shazia and Kazi, Majharoddin (2024) Stratifying Dermatological Illnesses Found in India: Non-Invasive Diagnostics Based on Residual Network and Support Vector Machine Integration. In: 5TH INTERNATIONAL CONFERENCE ON COMMUNICATION ENGINEERING AND COMPUTER SCIENCE (CIC-COCOS'24), 24-25/04/2024, Cihan University-Erbil.
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Abstract
The skin is the largest and most exposed organ which bears environmental conditions all the time. Timely examination and proper medication to the skin is equally essential to avoid further skin disease complications. With the advent of science and technology it shall now be possible to diagnose the type of the skin problem in a non-invasive way and decide the further line of treatment in the due course. The present article discusses the most common type of skin problems observed in India. Furthermore, it attempts to design a system using combination of AI techniques that cater the needs of dermatologists in detecting and treating the skin disorders. And finally discusses the outcomes of the system implementation.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Uncontrolled Keywords: | Dermatological Illness; ResNet101; ResNet50; ResNet152; Support Vector Machines; Data Augmentation |
| Subjects: | Q Science > QC Physics R Medicine > R Medicine (General) |
| Divisions: | Conferences > CIC-COCOS |
| Depositing User: | ePrints Depositor |
| Date Deposited: | 14 Apr 2025 07:26 |
| Last Modified: | 14 Apr 2025 07:26 |
| URI: | https://eprints.cihanuniversity.edu.iq/id/eprint/3261 |
