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IJCAI
1989
13 years 8 months ago
An Empirical Comparison of Pattern Recognition, Neural Nets, and Machine Learning Classification Methods
Classification methods from statistical pattern recognition, neural nets, and machine learning were applied to four real-world data sets. Each of these data sets has been previous...
Sholom M. Weiss, Ioannis Kapouleas
ICVGIP
2004
13 years 9 months ago
A Framework for Activity Recognition and Detection of Unusual Activities
In this paper we present a simple framework for activity recognition based on a model of multi-layered finite state machines, built on top of a low level image processing module f...
Dhruv Mahajan, Nipun Kwatra, Sumit Jain, Prem Kalr...
BC
2006
149views more  BC 2006»
13 years 7 months ago
Learning invariant object recognition in the visual system with continuous transformations
Abstract The cerebral cortex utilizes spatiotemporal continuity in the world to help build invariant representations. In vision, these might be representations of objects. The temp...
Simon M. Stringer, G. Perry, Edmund T. Rolls, J. H...
GIS
2007
ACM
14 years 1 months ago
Predicting future locations using clusters' centroids
As technology advances we encounter more available data on moving objects, thus increasing our ability to mine spatiotemporal data. We can use this data for learning moving object...
Sigal Elnekave, Mark Last, Oded Maimon
GECCO
2007
Springer
173views Optimization» more  GECCO 2007»
14 years 1 months ago
UCSpv: principled voting in UCS rule populations
Credit assignment is a fundamental issue for the Learning Classifier Systems literature. We engage in a detailed investigation of credit assignment in one recent system called UC...
Gavin Brown, Tim Kovacs, James A. R. Marshall