most citedHyperbolic Secant representation of the logistic function: Application to probabilistic Multiple Instance Learning for CT intracranial hemorrhage detection

8 citations · 8 across the 1 of their papers we have counts for

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1 paper

cs.LG2024★ 8 cited

Hyperbolic Secant representation of the logistic function: Application to probabilistic Multiple Instance Learning for CT intracranial hemorrhage detection

F. M. Castro-Macías, P. Morales-Álvarez, Y. Wu +2

Multiple Instance Learning (MIL) is a weakly supervised paradigm that has been successfully applied to many different scientific areas and is particularly well suited to medical im…