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We propose an evolutionary method for detection of vehicles in satellite imagery which involves a large number of simple elementary features and multiple detectors trained by genetic programming. The complete detection system is composed of several detectors that are chained into a cascade and successively filter out the negative examples. Each detector is a committee of genetic programming trees...
This paper reviews the existing work in genetic programming for object detection and image analysis. It shortly introduces the reader into the fundamentals of evolutionary computation and presents the basics of the genetic programming paradigm (GP), providing a rationale for the use of GP within computer vision and pattern recognition, particularly when applied to object detection and image analysis...
In this paper, we present a novel method for learning complex concepts/hypotheses directly from raw training data. The task addressed here concerns data-driven synthesis of recognition procedures for real-world object recognition. The method uses linear genetic programming to encode potential solutions expressed in terms of elementary operations, and handles the complexity of the learning task by...
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