This paper presents an interactive system for the annotation of brain anatomical structures in Magnetic Resonance Images. The system is based on hybrid knowledge and techniques. Fi...
Large collaborative datasets offer the challenging opportunity of creating systems capable of extracting knowledge in the presence of noisy data. In this work we explore the abili...
Emily Moxley, Jim Kleban, Jiejun Xu, B. S. Manjuna...
In this paper, we present a novel approach to classify texture collections. This approach does not require experts to provide annotated training set. Given the image collection, w...
Lei Qin, Qingfang Zheng, Shuqiang Jiang, Qingming ...
Nowadays, images have become widely available on the World Wide Web (WWW). It’s essential to develop effective ways for managing and retrieving such abundant images. Advantageou...
We present a system for estimating location and orientation of a person’s head, from depth data acquired by a low quality device. Our approach is based on discriminative random r...