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AGI
2011
13 years 12 days ago
Imprecise Probability as a Linking Mechanism between Deep Learning, Symbolic Cognition and Local Feature Detection in Vision Pro
A novel approach to computer vision is outlined, involving the use of imprecise probabilities to connect a deep learning based hierarchical vision system with both local feature de...
Ben Goertzel
ICPR
2010
IEEE
14 years 21 days ago
Monogenic Binary Pattern (MBP): A Novel Feature Extraction and Representation Model for Face Recognition
A novel feature extraction method, namely monogenic binary pattern (MBP), is proposed in this paper based on the theory of monogenic signal analysis, and the histogram of MBP (HMB...
Meng Yang, Lei Zhang, Lin Zhang, David Zhang
KDD
2005
ACM
149views Data Mining» more  KDD 2005»
14 years 2 months ago
A distributed learning framework for heterogeneous data sources
We present a probabilistic model-based framework for distributed learning that takes into account privacy restrictions and is applicable to scenarios where the different sites ha...
Srujana Merugu, Joydeep Ghosh
TIP
2008
142views more  TIP 2008»
13 years 8 months ago
Image Feature Localization by Multiple Hypothesis Testing of Gabor Features
Several novel and particularly successful object and object category detection and recognition methods based on image features, local descriptions of object appearance, have recent...
Jarmo Ilonen, Joni-Kristian Kamarainen, Pekka Paal...
CAIP
2009
Springer
221views Image Analysis» more  CAIP 2009»
14 years 3 months ago
Model Based Analysis of Face Images for Facial Feature Extraction
This paper describes a comprehensive approach to extract a common feature set from the image sequences. We use simple features which are easily extracted from a 3D wireframe model ...
Zahid Riaz, Christoph Mayer, Michael Beetz, Bernd ...