Explanation and Use of Uncertainty Quantified by Bayesian Neural Network Classifiers for Breast Histopathology Images

Despite the promise of Convolutional neural network (CNN) based classification models for histopathological images, it is infeasible to quantify its uncertainties. Moreover, CNNs may suffer from overfitting when the data is biased. We show that Bayesian-CNN can overcome these limitations by regulari...

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Veröffentlicht in:	arXiv.org 2021-11
Hauptverfasser:	Thiagarajan, Ponkrshnan, Khairnar, Pushkar, Ghosh, Susanta
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Artificial neural networks Bayesian analysis Computer Science - Computer Vision and Pattern Recognition Computer Science - Learning Convergence Image classification Machine learning Mathematical models Neural networks Parameters Uncertainty
Online-Zugang:	Volltext
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