In this paper, we propose a generative model-based approach for audio-visual event classification. This approach is based on a new unsupervised learning method using an extended p...
Ming Li, Sanqing Hu, Shih-Hsi Liu, Sung Baang, Yu ...
This paper introduces a novel way to leverage the implicit geometry of sparse local features (e.g. SIFT operator) for the purposes of object detection and segmentation. A two-clas...
Named Entity Recognition and Classification is being studied for last two decades. Since semantic features take huge amount of training time and are slow in inference, the existing...
Siddhartha Jonnalagadda, Robert Leaman, Trevor Coh...
The creation of huge databases coming from both restoration of existing analogue archives and new content is demanding fast and more and more reliable tools for content analysis a...
Digital music distribution industry has seen a tremendous growth in resent years. Tasks such us automatic music genre discrimination address new and exciting research challenges. A...