This paper presents a semi-supervised learning (SSL) approach to find similarities of images using statistics of local matches. SSL algorithms are well known for leveraging a larg...
The required amount of labeled training data for object detection and classification is a major drawback of current methods. Combining labeled and unlabeled data via semisupervise...
An adaptive semi-supervised ensemble method, ASSEMBLE, is proposed that constructs classification ensembles based on both labeled and unlabeled data. ASSEMBLE alternates between a...
In this paper, we present the LIP6 annotation models for the ImageCLEFannotation 2010 task. We study two methods to train and merge the results of different classifiers in order to...
Ali Fakeri-Tabrizi, Sabrina Tollari, Nicolas Usuni...
Visual understanding is often based on measuring similarity between observations. Learning similarities specific to a certain perception task from a set of examples has been show...
Michael Bronstein, Alexander Bronstein, Nikos Para...