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

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Francisco M. Castro-Macías , Pablo Morales-Álvarez , Yunan Wu , Rafael Molina , Aggelos K. Katsaggelos ·

YOU? · · 2024 · Open Access · · DOI: https://doi.org/10.1016/j.artint.2024.104115

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Probabilistic logic Representation (politics) Gaussian Computer science Artificial intelligence Logistic function Function (biology) Posterior probability Mathematics Applied mathematics Machine learning Mathematical optimization Bayesian probability Evolutionary biology Quantum mechanics Law Physics Politics Political science Biology

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Type: article
Language: en
Landing Page: https://doi.org/10.1016/j.artint.2024.104115
OA Status: hybrid
Cited By: 3
References: 54
Related Works: 10
OpenAlex ID: https://openalex.org/W4392860069

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DOI: https://doi.org/10.1016/j.artint.2024.104115

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

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Language: en

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Publication year: 2024

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Publication date: 2024-03-15

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Authors: Francisco M. Castro-Macías, Pablo Morales-Álvarez, Yunan Wu, Rafael Molina, Aggelos K. Katsaggelos

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Landing page: https://doi.org/10.1016/j.artint.2024.104115

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Concepts: Probabilistic logic, Representation (politics), Gaussian, Computer science, Artificial intelligence, Logistic function, Function (biology), Posterior probability, Mathematics, Applied mathematics, Machine learning, Mathematical optimization, Bayesian probability, Evolutionary biology, Quantum mechanics, Law, Physics, Politics, Political science, Biology

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Cited by: 3

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