A two-stage fine-tuning method, called CELD, reports 91% accuracy for three-class fundus image classification, but the claimed anti-forgetting benefit is not demonstrated.
In: Proceedings of the IEEE 5th International Conference on Cybernetics, Cognition and Machine Learning Applications (ICC- CMLA)
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Adaptive Class Learning to Screen Diabetic Disorders in Fundus Images of Eye
A two-stage fine-tuning method, called CELD, reports 91% accuracy for three-class fundus image classification, but the claimed anti-forgetting benefit is not demonstrated.