We present an approach to low-level vision that combines two main ideas: the use of convolutional networks as an image processing architecture and an unsupervised learning procedu...
This paper presents a Bayesian framework for multi-cue 3D object tracking of deformable objects. The proposed spatio-temporal object representation involves a set of distinct linea...
We present a question answering (QA) system which learns how to detect and rank answer passages by analyzing questions and their answers (QA pairs) provided as training data. We b...
We present the machine learning framework that we are developing, in order to support explorative search for non-trivial linguistic configurations in low-density languages (langua...
In this paper we report our work on building a POS tagger for a morphologically rich language- Hindi. The theme of the research is to vindicate the stand that- if morphology is st...