This paper presents an approach for establishing correspondencesin time and in space between two differentvideo sequences of the same dynamic scene, recorded by stationary uncalib...
In this work, a generalized method for learning from sequence of unlabelled data points based on unsupervised order-preserving regression is proposed. Sequence learning is a funda...
We present a novel framework for tracking of a long sequence of human activities, including the time instances of change from one activity to the next, using a closed-loop, non-li...
—This paper concerns an efficient algorithm for learning in the limit a special type of regular languages called strictly locally testable languages from positive data, and its a...
The Smith-Waterman (SW) algorithm is one of the widely used algorithms for sequence alignment in computational biology. With the growing size of the sequence database, there is alw...