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Genetic Programming for Object Detection: A Two-Phase Approach with an Improved Fitness Function
2007
ELCVIA Electronic Letters on Computer Vision and Image Analysis
This paper describes two innovations that improve the efficiency and effectiveness of a genetic programming approach to object detection problems. The approach uses genetic programming to construct object detection programs that are applied, in a moving window fashion, to the large images to locate the objects of interest. The first innovation is to break the GP search into two phases with the first phase applied to a selected subset of the training data, and a simplified fitness function. The
doi:10.5565/rev/elcvia.135
fatcat:owqdtzzsjrhhzgqclnhjtwmfwa