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About Progressive Transfer Learning and Adversarial Domain Adaptation For Cross-Domain Skin Disease Classification
1) The document presents two methods for cross-domain skin disease recognition using deep learning: progressive transfer learning and adversarial domain adaptation. 2) Progressive transfer learning fine-tunes a pre-trained CNN model on one skin disease dataset, then further fine-tunes it on a second dataset to improve performance across domains. 3) Adversarial domain adaptation uses cycle-consistent GANs to transform images from one domain to match the style of another domain, improving the model's ability to recognize diseases across different image collections.
Detailed Information
| Author: | ['Hassan Shafique'] |
|---|---|
| Publication Year: | 2020 |
| Pages: | 15 |
| Language: | English |
| Format: | |
| Price: | FREE |
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