PRIVACY-PRESERVING EFFICIENT FEDERATED DEEP LEARNING MODEL FOR SKIN LESION CLASSIFICATION /
Bewaard in:
| Hoofdauteur: | |
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| Coauteur: | |
| Formaat: | Boek |
| Taal: | Engels |
| Gepubliceerd in: |
Dhaka :
CSE DEPT. MIST,
c2026.
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| Onderwerpen: | |
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Gelijkaardige items: PRIVACY-PRESERVING EFFICIENT FEDERATED DEEP LEARNING MODEL FOR SKIN LESION CLASSIFICATION /
- ISCHEMIC STROKE LESION SEGMENTATION FROM DIFFUSION-WEIGHTED MRI USING DEEP ENSEMBLE LEARNING / /
- SKIN LESION ANALYSIS USING HYBRID MACHINE LEARNING TECHNIQUES FOR EARLY DETECTION OF SKIN CANCER /
- A DEEP LEARNING-BASED STACKING APPROACH FOR SKIN ALLERGY CLASSIFICATION /
- DETECTING THE FETAL HEALTH CONDITION USING FEDERATED LEARNING APPROACH WITH INCENTIVE-BASED REWARDS SYSTEM /
- MEDSKIN: A MACHINE LEARNING APPROACH FOR SKIN DISEASE CLASSIFICATION /
- ADVERSARIAL-AWARE BI-LEVEL UNET AND SEMI-SUPERVISED LEARNING FOR ENHANCING SKIN LESION SEGMENTATION /