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ECCV
2010
Springer
13 years 7 months ago
MIForests: Multiple-Instance Learning with Randomized Trees
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
Christian Leistner, Amir Saffari, Horst Bischof
AROBOTS
2007
159views more  AROBOTS 2007»
13 years 7 months ago
Structure-based color learning on a mobile robot under changing illumination
— A central goal of robotics and AI is to be able to deploy an agent to act autonomously in the real world over an extended period of time. To operate in the real world, autonomo...
Mohan Sridharan, Peter Stone
BMCBI
2006
134views more  BMCBI 2006»
13 years 7 months ago
A statistical score for assessing the quality of multiple sequence alignments
Background: Multiple sequence alignment is the foundation of many important applications in bioinformatics that aim at detecting functionally important regions, predicting protein...
Virpi Ahola, Tero Aittokallio, Mauno Vihinen, Esa ...
CVIU
2006
162views more  CVIU 2006»
13 years 7 months ago
Unsupervised scene analysis: A hidden Markov model approach
This paper presents a new approach to scene analysis, which aims at extracting structured information from a video sequence using directly low-level data. The method models the se...
Manuele Bicego, Marco Cristani, Vittorio Murino
IVS
2008
145views more  IVS 2008»
13 years 7 months ago
Towards a taxonomy of movement patterns
A review of research that has been carried out on data mining and visual analysis of movement patterns suggests that there is little agreement on the relevant types of movement pa...
Somayeh Dodge, Robert Weibel, Anna-Katharina Laute...