We propose a method to learn heterogeneous models of object classes for visual recognition. The training images contain a preponderance of clutter and learning is unsupervised. Ou...
We present an approach for automatic detection of topic change. Our approach is based on the analysis of statistical features of topics in time-sliced corpora and their dynamics ov...
In this paper we present a detailed analysis of the performance of the Decision Theoretic Read Delay (DTRD) optimistic synchronisation algorithm for simulations of Multistems. We ...
Michael Lees, Brian Logan, Dan Chen, Ton Oguara, G...
Mark-recapture models have for many years been used to estimate the unknown sizes of animal and bird populations. In this article we adapt a finite mixture mark-recapture model i...
A vision-based machine learner is presented that learns characteristic hand and object movement patterns for using certain objects, and uses this information to recreate the "...
Andreya Piplica, Alexandra Olivier, Allison Petros...