Genetic Algorithms for Automatic Classification of Moving Objects

O David-Tabibi, N. S Netanyahu, Y Rosenberg, M Shimoni

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


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.
Original languageAmerican English
Title of host publicationThe 12th annual conference companion on Genetic and evolutionary computation
StatePublished - 2010

Bibliographical note

Place of conference:Portland, Oregon, USA


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