Deep Interpretable Classification and Weakly-Supervised Segmentation of Histology Images via Max-Min Uncertainty.
Soufiane BelharbiJérôme RonyJose DolzIsmail Ben AyedLuke McCaffreyEric GrangerPublished in: CoRR (2020)
Keyphrases
- weakly supervised
- max min
- segmentation algorithm
- segmentation method
- superpixels
- fully supervised
- image classification
- test images
- image features
- input image
- image retrieval
- image segmentation
- ground truth
- image regions
- semantic segmentation
- image database
- multiple images
- medical images
- robust optimization
- object segmentation
- multiple objects
- object class
- training samples
- region of interest
- support vector
- supervised learning
- bounding box
- machine learning
- feature vectors
- min max
- feature space
- support vector machine
- feature selection
- feature extraction
- object recognition
- object detectors
- color histogram
- text classification
- labeled data
- active contours