2015
Weakly-Supervised Structured Output Learning With Flexible and Latent Graphs Using High-Order Loss Functions
ICCV 2015poster
We introduce two new structured output models that use a latent graph, which is flexible in terms of the number of nodes and structure, where the training process minimises a high-order loss function using a weakly annotated training set. These models are developed in the context of microscopy imagi…