Our objective is to improve the performance of keyword based image search engines by re-ranking their baseline results. To this end, we address three limitations of existing searc...
We address the problem of weakly supervised semantic segmentation. The training images are labeled only by the classes they contain, not by their location in the image. On test im...
Alexander Vezhnevets, Vittorio Ferrari, Joachim M....
We present a method for automatic extraction of frames from .a dependency graph. Our method uses machine learning applied to a dependency tree to assign frames and assign frame ele...
This paper reports our research in the Web page filtering process in specialized search engine development. We propose a machine-learning-based approach that combines Web content a...
Clustering is a form of unsupervised machine learning. In this paper, we proposed the DBRS_O method to identify clusters in the presence of intersected obstacles. Without doing an...