SkinNet: A Hybrid Convolutional Learning Approach and Transformer Module Through Bi-directional Feature Fusion
Author:
Affiliation:
1. Meybod University,Deprtement of biomedical enginering,Iran
2. Persian Gulf University,Iran
3. Qufu Normal University,China
4. Bu Ali Sina University,Department of Computer Engineeeing,Hamedan,Iran
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9885260/9885243/09885591.pdf?arnumber=9885591
Reference31 articles.
1. Melanoma Classification Using a Novel Deep Convolutional Neural Network with Dermoscopic Images;kaur;SENSORS,2018
2. Neural Architecture Search for Skin Lesion Classification
3. A hybrid deep transfer learning-based approach for Parkinson's disease classification in surface electromyography signals
4. Early convolutions help transformers see better;xiao;Proc Adv Neural Inf Process Syst,2021
5. Attention Residual Learning for Skin Lesion Classification
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1. DEEPSCAN: Integrating Vision Transformers for Advanced Skin Lesion Diagnostics;The Open Dermatology Journal;2024-03-21
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