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» Selective Attention Improves Learning
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ICCV
2005
IEEE
16 years 2 months ago
A Supervised Learning Framework for Generic Object Detection in Images
In recent years Kernel Principal Component Analysis (Kernel PCA) has gained much attention because of its ability to capture nonlinear image features, which are particularly impor...
Saad Ali, Mubarak Shah
89
Voted
ICIP
2002
IEEE
15 years 5 months ago
An iterative algorithm for context selection in adaptive entropy coders
Context-based adaptive entropy coding is an essential feature of modern image compression algorithms; however, the design of these coders is non-trivial due to the balance that mu...
Tong Jin, Jacques Vaisey
118
Voted
ECCV
2010
Springer
15 years 3 months ago
Clustering Complex Data with Group-Dependent Feature Selection
Abstract. We describe a clustering approach with the emphasis on detecting coherent structures in a complex dataset, and illustrate its effectiveness with computer vision applicat...
118
Voted
IJCAI
2007
15 years 2 months ago
Detection of Cognitive States from fMRI Data Using Machine Learning Techniques
Over the past decade functional Magnetic Resonance Imaging (fMRI) has emerged as a powerful technique to locate activity of human brain while engaged in a particular task or cogni...
Vishwajeet Singh, Krishna P. Miyapuram, Raju S. Ba...
148
Voted
ESANN
2006
15 years 2 months ago
Random Forests Feature Selection with K-PLS: Detecting Ischemia from Magnetocardiograms
Random Forests were introduced by Breiman for feature (variable) selection and improved predictions for decision tree models. The resulting model is often superior to AdaBoost and ...
Long Han, Mark J. Embrechts, Boleslaw K. Szymanski...