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Segmentation with mixed supervision: Confidence maximization helps knowledge distillation

Despite achieving promising results in a breadth of medical image segmentation tasks, deep neural networks require large training datasets with pixel-wise annotations. Obtaining these curated datasets is a cumbersome process which limits the …

Detection guided deconvolutional network for hierarchical feature learning

Deep learning models have gained significant interest as a way of building hierarchical image representation. However, current models still perform far behind human vision system because of the lack of selective property, the lack of high-level …

Learning representative and discriminative image representation by deep appearance and spatial coding

How to build a suitable image representation remains a critical problem in computer vision. Traditional Bag-of-Feature (BoF) based models build image representation by the pipeline of local feature extraction, feature coding and spatial pooling. …

Adaptive spatial partition learning for image classification

Spatial Pyramid Matching is a successful extension of bag-of-feature model to embed spatial information of local features, in which the image is divided into a sequence of increasingly finer girds, and the grids are taken as uniform spatial …