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» Machine Learning, Machine Vision, and the Brain
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ICCV
2003
IEEE
16 years 6 months ago
A Sparse Probabilistic Learning Algorithm for Real-Time Tracking
This paper addresses the problem of applying powerful pattern recognition algorithms based on kernels to efficient visual tracking. Recently Avidan [1] has shown that object recog...
Oliver M. C. Williams, Andrew Blake, Roberto Cipol...
CCIA
2005
Springer
15 years 9 months ago
Comparison of Strategies Based on Evolutionary Computation for the Design of Similarity Functions
One of the main keys in case-based reasoning system is the retrieval phase, where the most similar cases are retrieved by means of a similarity function. According to the problem, ...
Albert Fornells-Herrera, J. Camps Dausà, El...
TMI
2010
206views more  TMI 2010»
14 years 10 months ago
Random Subspace Ensembles for fMRI Classification
Classification of brain images obtained through functional magnetic resonance imaging (fMRI) poses a serious challenge to pattern recognition and machine learning due to the extrem...
Ludmila I. Kuncheva, Juan José Rodrí...
MIR
2005
ACM
129views Multimedia» more  MIR 2005»
15 years 9 months ago
Tracking concept drifting with an online-optimized incremental learning framework
Concept drifting is an important and challenging research issue in the field of machine learning. This paper mainly addresses the issue of semantic concept drifting in time series...
Jun Wu, Dayong Ding, Xian-Sheng Hua, Bo Zhang
CVPR
2012
IEEE
13 years 9 months ago
Stream-based Joint Exploration-Exploitation Active Learning
Learning from streams of evolving and unbounded data is an important problem, for example in visual surveillance or internet scale data. For such large and evolving real-world data...
Chen Change Loy, Timothy M. Hospedales, Tao Xiang,...