Deep interpretable classification and weakly-supervised segmentation of histology images via max-min uncertainty

/in , , /by
Deep interpretable classification and weakly-supervised segmentation of histology images via max-min uncertainty

Belharbi, Soufiane, Rony, Jérôme, Dolz, Jose, Ben Ayed, Ismail, McCaffrey, Luke and Granger, Eric.

Journal 2022

You might also like
Emotion recognition with spatial attention and temporal softmax pooling
Texture CNN for thermoelectric metal pipe image classification
A dual-staged classification-selection approach for automated update of biometric templates
Experimental and numerical modelling of symmetrical four-branch supercritical cross junction flow
Familiarity discrimination of radar pulses
Evaluation of an Integrated Minimally Interactive Tool for the Segmentation of Relevant Oar in Lung Cancer
Speaker adaptation using the i-vector technique for bottleneck features
Unsupervised feature learning for environmental sound classification using weighted cycle-consistent generative adversarial network