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IJCV
2008
241views more  IJCV 2008»
15 years 7 months ago
Object Class Recognition and Localization Using Sparse Features with Limited Receptive Fields
We investigate the role of sparsity and localized features in a biologically-inspired model of visual object classification. As in the model of Serre, Wolf, and Poggio, we first a...
Jim Mutch, David G. Lowe
IJCV
2000
149views more  IJCV 2000»
15 years 6 months ago
Recognition without Correspondence using Multidimensional Receptive Field Histograms
The appearance of an object is composed of local structure. This local structure can be described and characterized by a vector of local features measured by local operators such a...
Bernt Schiele, James L. Crowley
PRESENCE
1998
78views more  PRESENCE 1998»
15 years 6 months ago
The Effects of Metals and Interfering Fields on Electromagnetic Trackers
The operation of six degree-of-freedom electromagnetic trackers is based on the spatial properties of the electromagnetic fields generated by three small coils. Anything in the e...
Mark A. Nixon, Bruce C. McCallum, W. Richard Frigh...
IDEAL
2010
Springer
15 years 5 months ago
Typed Linear Chain Conditional Random Fields and Their Application to Intrusion Detection
Intrusion detection in computer networks faces the problem of a large number of both false alarms and unrecognized attacks. To improve the precision of detection, various machine l...
Carsten Elfers, Mirko Horstmann, Karsten Sohr, Ott...
CVPR
2007
IEEE
16 years 9 months ago
Region Classification with Markov Field Aspect Models
Considerable advances have been made in learning to recognize and localize visual object classes. Simple bag-offeature approaches label each pixel or patch independently. More adv...
Jakob J. Verbeek, Bill Triggs