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AGI
2011
14 years 10 months 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
CVPR
2003
IEEE
16 years 8 months ago
Extracting Dense Features for Visual Correspondence with Graph Cuts
We present a method for extracting dense features from stereo and motion sequences. Our dense feature is defined symmetrically with respect to both images, and it is extracted dur...
Olga Veksler
PKDD
2007
Springer
196views Data Mining» more  PKDD 2007»
16 years 23 days ago
Speeding Up Feature Subset Selection Through Mutual Information Relevance Filtering
A relevance filter is proposed which removes features based on the mutual information between class labels and features. It is proven that both feature independence and class condi...
Gert Van Dijck, Marc M. Van Hulle
CVPR
2007
IEEE
16 years 8 months ago
Segmental Hidden Markov Models for View-based Sport Video Analysis
We present a generative model approach to explore intrinsic semantic structures in sport videos, e.g., the camera view in American football games. We will invoke the concept of se...
Yi Ding, Guoliang Fan
WACV
2005
IEEE
16 years 7 days ago
Automatic Recognition of Colloquial Australian Sign Language
This paper presents an automatic Australian sign language (Auslan) recognition system, which tracks multiple target objects (the face and hands) throughout an image sequence and e...
Eun-Jung Holden, Gareth Lee, Robyn A. Owens