Traditional supervised visual learning simply asks annotators “what” label an image should have. We propose an approach for image classification problems requiring subjective...
In this paper, a novel genetically-inspired visual learning method is proposed. Given the training images, this general approach induces a sophisticated feature-based recognition s...
We propose a probabilistic graphical model to represent weakly annotated images1 . This model is used to classify images and automatically extend existing annotations to new image...
Abstract. An important aspect of discourse understanding and generation involves the recognition and processing of discourse relations. These are conveyed by discourse connectives,...
Eleni Miltsakaki, Livio Robaldo, Alan Lee, Aravind...
This paper focuses on one of the Image CLEF Photo tasks at which the MRIM research group of the LIG participated: the Visual Concept Detection and Annotation. For this task, we app...