Feature similarity includes both the invariance of marginal distributions and the closeness of conditional distributions given the desired response $y$ (e. g., class labels).
Multi-label classification of chest X-ray images is frequently performed using discriminative approaches, i. e. learning to map an image directly to its binary labels.
These shortcut connections improve the performance and it is hypothesized that this is due to mitigating effects on the vanishing gradient problem and the ability of the model to combine feature maps from earlier and later layers.
Standard short-cut connections are connections between layers in deep neural networks which skip at least one intermediate layer.
Detecting objects and estimating their pose remains as one of the major challenges of the computer vision research community.
A visual-relational knowledge graph (KG) is a multi-relational graph whose entities are associated with images.