IDR - IIT Kharagpur
Lightweight, Explainable and Privacy-Preserving Federated AI Frameworks for Early Cervical Cancer Detection on Consumer-Grade Devices
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| dc.contributor.author | Mukhopadhyay, Sabyasachi | |
| dc.date.accessioned | 2026-05-12T05:18:49Z | |
| dc.date.available | 2026-05-12T05:18:49Z | |
| dc.date.issued | 2026-01 | |
| dc.identifier.govdoc | NB19173 | |
| dc.identifier.uri | http://127.0.0.1/xmlui/handle/123456789/17276 | |
| dc.language.iso | en | en_US |
| dc.publisher | IIT Kharagpur | en_US |
| dc.subject | Cervical Precancer Detection | en_US |
| dc.subject | Personalized Federated Learning | en_US |
| dc.subject | Lightweight Deep Learning | en_US |
| dc.subject | Geometric Deep Learning | en_US |
| dc.subject | Explainable AI 2.0 | en_US |
| dc.title | Lightweight, Explainable and Privacy-Preserving Federated AI Frameworks for Early Cervical Cancer Detection on Consumer-Grade Devices | en_US |
| dc.type | Thesis | en_US |
