With the exponential growth of moving objects data to the Gigabyte range, it has become critical to develop effective techniques for indexing, updating, and querying these massive ...
Jens Dittrich, Lukas Blunschi, Marcos Antonio Vaz ...
In this paper, we propose a novel boosted mixture learning (BML) framework for Gaussian mixture HMMs in speech recognition. BML is an incremental method to learn mixture models fo...
One of the most challenging aspects of concurrent mapping and localization (CML) is the problem of data association. Because of uncertainty in the origins of sensor measurements, i...
John J. Leonard, Paul M. Newman, Richard J. Rikosk...
We present techniques to semi-automatically discover Recurrent Visual Semantics (RVS) -the repetitive appearance of visually similar elements such as objects and scenes- in consum...
Alejandro Jaimes, Ana B. Benitez, Shih-Fu Chang, A...
This paper discusses the question: Can we improve the recognition of objects by using their spatial context? We start from Bag-of-Words models and use the Pascal 2007 dataset. We u...
Arnold W. M. Smeulders, Jasper R. R. Uijlings, Rem...