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GECCO
2010
Springer

Genetic algorithms for automatic classification of moving objects

9 years 11 days ago
Genetic algorithms for automatic classification of moving objects
This paper presents an integrated approach, combining a state-of-the-art commercial object detection system and genetic algorithms (GA)-based learning for automatic object classification. Specifically, the approach is based on applying weighted nearest neighbor classification to feature vectors extracted from the detected objects, where the weights are evolved due to GA-based learning. Our results demonstrate that this GA-based approach is considerably superior to other standard classification methods. Categories and Subject Descriptors: I.2.6 [Artificial Intelligence]: Learning--Parameter learning General Terms: Algorithms.
Omid David-Tabibi, Nathan S. Netanyahu, Yoav Rosen
Added 09 Nov 2010
Updated 09 Nov 2010
Type Conference
Year 2010
Where GECCO
Authors Omid David-Tabibi, Nathan S. Netanyahu, Yoav Rosenberg, Moshe Shimoni
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