Kaur, Tejinder, Thakur, Anjali, Kaur, Daljeet, Dhillon, Sehaj Singh
ORCID: https://orcid.org/0009-0007-3543-9856, Chaudhary, Vijeta and Gupta, Jotesh
(2026)
Deep Learning-based Efficient Classification of Skin Diseases using Convolutional Neural Networks.
In: 2026 International Conference on AI-Driven Smart Systems and Ubiquitous Computing (ICAUC), 19 January 2026 - 21 January 2026, Pathum Thani, Thailand.
Abstract
A greater awareness of the importance of early identification in improving patient outcomes has also led to researchers looking into new technology and techniques, which is progressing the disciplines of dermatology and cancer in general. The collaborative efforts of interdisciplinary teams comprising dermatologists, computer scientists, and medical specialists demonstrate the intentional commitment to enhancing the diagnostic capabilities for skin conditions, which will ultimately benefit people and healthcare systems throughout the world. This research presents a new technique for diagnosing skin diseases that emphasizes early detection. Early identification is crucial since it allows for prompt intervention and presents chances for less intrusive and more efficient treatment techniques.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Uncontrolled Keywords: | CNN | Deep Learning | Machine Learning | Monkeypox | Skin Disease |
| Subjects: | Physical, Life and Health Sciences > Medicine |
| Depositing User: | Mr. Syed Anas |
| Date Deposited: | 21 May 2026 07:02 |
| Last Modified: | 21 May 2026 07:02 |
| Official URL: | https://doi.org/10.1109/ICAUC68182.2026.11441147 |
| URI: | https://pure.jgu.edu.in/id/eprint/11354 |
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