4 citations · 5 across the 4 of their papers we have counts for
4 papers
Unsupervised pre-training helps to conserve views from input distribution
Nicolas Pinchaud
We investigate the effects of the unsupervised pre-training method under the perspective of information theory. If the input distribution displays multiple views of the supervision…
Information theoretic learning of robust deep representations
Nicolas Pinchaud
We propose a novel objective function for learning robust deep representations of data based on information theory. Data is projected into a feature-vector space such that the mutu…
Weakly supervised training of pixel resolution segmentation models on whole slide images
Nicolas Pinchaud
We present a novel approach to train pixel resolution segmentation models on whole slide images in a weakly supervised setup. The model is trained to classify patches extracted fro…
Segmenting Potentially Cancerous Areas in Prostate Biopsies using Semi-Automatically Annotated Data
Nikolay Burlutskiy, Nicolas Pinchaud, Feng Gu +7
Gleason grading specified in ISUP 2014 is the clinical standard in staging prostate cancer and the most important part of the treatment decision. However, the grading is subjective…