In this paper, we present an automatic classification framework combining appearance based features and Hidden Markov Models (HMM) to detect unusual events in image sequences. One...
Recent work in supervised learning of term-based retrieval models has shown significantly improved accuracy can often be achieved via better model estimation [2, 10, 11, 17]. In ...
We seek to both detect and segment objects in images. To exploit both local image data as well as contextual information, we introduce Boosted Random Fields (BRFs), which use boos...
Antonio Torralba, Kevin P. Murphy, William T. Free...
—In this paper, we propose a circular blurred shape model descriptor to deal with the problem of symbol detection and classification as a particular case of object recognition. ...
This paper employs the network perspective to study patterns and structures of intraorganizational learning networks. The theoretical background draws from cognitive theories, the...