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» Learning Mid-Level Features For Recognition
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DICTA
2009
13 years 8 months ago
SIFTing the Relevant from the Irrelevant: Automatically Detecting Objects in Training Images
Many state-of-the-art object recognition systems rely on identifying the location of objects in images, in order to better learn its visual attributes. In this paper, we propose fo...
Edmond Zhang, Michael Mayo
BLISS
2008
IEEE
14 years 2 months ago
HLAC Approach to Automatic Object Counting
Counting (identical) objects in images is a simple yet fundamental recognition task that requires exhaustive human effort. Automation of this task would reduce the human load sign...
Takumi Kobayashi, Tadaaki Hosaka, Shu Mimura, Taka...
KDD
2010
ACM
310views Data Mining» more  KDD 2010»
13 years 11 months ago
An integrated machine learning approach to stroke prediction
Stroke is the third leading cause of death and the principal cause of serious long-term disability in the United States. Accurate prediction of stroke is highly valuable for early...
Aditya Khosla, Yu Cao, Cliff Chiung-Yu Lin, Hsu-Ku...
PR
2010
129views more  PR 2010»
13 years 6 months ago
Parsimonious reduction of Gaussian mixture models with a variational-Bayes approach
Aggregating statistical representations of classes is an important task for current trends in scaling up learning and recognition, or for addressing them in distributed infrastruc...
Pierrick Bruneau, Marc Gelgon, Fabien Picarougne
EXPERT
2010
145views more  EXPERT 2010»
13 years 5 months ago
Interaction Analysis with a Bayesian Trajectory Model
Human behavior recognition is one of the most important and challenging objectives performed by intelligent vision systems. Several issues must be faced in this domain ranging fro...
Alessio Dore, Carlo S. Regazzoni