HIGHLIGHTS
- who: Retinopathy Classification and colleagues from the Department of Computer Science, Aalto University, Aalto, Finland have published the research: Uncertainty-aware Deep Learning Methods for Robust Diabetic Retinopathy Classification, in the Journal: (JOURNAL)
- what: The authors derive a connection between entropy-based uncertainty measure and classifier risk from which the authors develop a novel uncertainty measure. The common aspect among the works focusing on robust methods is the use of uncertainty information to simulate a referral process, introduced by Leibig et_al . They observed that the approximate Bayesian methods outperformed the standard neural_network in all the . . .
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