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Advancing Glaucoma Diagnosis: Employing Confidence-Calibrated Label Smoothing Loss for Model Calibration

Objective: The aim of our research is to enhance the calibration of machine learning models for glaucoma classification through a specialized loss function named Confidence-Calibrated Label Smoothing (CC-LS) loss. This approach is specifically designed to refine model calibration without compromisin...

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Autori principali: Midhula Vijayan, PhD, Deepthi Keshav Prasad, PhD, Venkatakrishnan Srinivasan, MTech
Natura: Artigo
Lingua:Inglês
Pubblicazione: Elsevier 2024-11-01
Serie:Ophthalmology Science
Soggetti:
Glaucoma
Deep learning
Model calibration
EfficientNet
Loss function
Accesso online:http://www.sciencedirect.com/science/article/pii/S2666914524000915
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