| Autor: |
Subapriya. V., Pushpa, P. N., Sandi, Arshin Jose, Xavier, Aleena, Varghese, Joel Joys |
| Předmět: |
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| Zdroj: |
Turkish Online Journal of Qualitative Inquiry; 2021, Vol. 12 Issue 6, p9136-9141, 6p |
| Abstrakt: |
Skin diseases are more frequent among the people across the globe because of increased air pollution, medicinal intakes, air pollution, genetics etc. Also many researches state that people provide less importance to skin disease during the initial stage which medicinal treatment complex. In the existing approach, the skin diseases are inspected manually from the biopsy results, which always have the risk of human dependency and less accurate prediction. To address this problem statement, in this paper we propose a computer vision and deep learning based technique to inspect and predict skin diseases at the early stage. For deep learning based classifier we have used convolutional neural network (CNN). Thus our proposed would have a greater impact towards society benefits thus helping people among rural locations in where access to dermatologists are less. For experimental results, we use jupiter tool with python script for image analysis and prediction. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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