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CIMCA
2005
IEEE
14 years 2 months ago
Fuzzy Inference Model for Learning from Experiences and Its Application to Robot Navigation
A fuzzy inference model for learning from experiences (FILE) is proposed. The model can learn from experience data obtained by trial-and-error of a task and it can stably learn fr...
Manabu Gouko, Yoshihiro Sugaya, Hirotomo Aso
ICMI
2009
Springer
146views Biometrics» more  ICMI 2009»
14 years 3 months ago
Learning from preferences and selected multimodal features of players
The influence of multimodal sources of input data to the construction of accurate computational models of user preferences is investigated in this paper. The case study presented...
Georgios N. Yannakakis
ISBI
2009
IEEE
14 years 3 months ago
Reduction of Distortions in MRSI Using a New Signal Model
We propose a new reconstruction scheme for magnetic resonance spectroscopic imaging (MRSI) signal based on minimizing the spatial total variation (TV) integrated with the 1 -norm ...
Ramin Eslami, Mathews Jacob
ICASSP
2010
IEEE
13 years 6 months ago
Learning from other subjects helps reducing Brain-Computer Interface calibration time
A major limitation of Brain-Computer Interfaces (BCI) is their long calibration time, as much data from the user must be collected in order to tune the BCI for this target user. I...
Fabien Lotte, Cuntai Guan
CVPR
2011
IEEE
13 years 17 days ago
Learning People Detection Models from Few Training Samples
People detection is an important task for a wide range of applications in computer vision. State-of-the-art methods learn appearance based models requiring tedious collection and ...
Leonid Pishchulin, Christian Wojek, Arjun Jain, Th...