2003

referat

angielski

EN In this paper, a novel genetically-inspired visual learning method is proposed. Given the training images, this general approach induces a sophisticated feature-based recognition system, by using cooperative coevolution and linear genetic programming for the procedural representation of feature extraction agents. The paper describes the learning algorithm and provides a firm rationale for its design. An extensive experimental evaluation, on the demanding real-world task of object recognition in synthetic aperture radar (SAR) imagery, shows the competitiveness of the proposed approach with human-designed recognition systems.

332 - 343

10.1007/3-540-45105-6_39

https://link.springer.com/chapter/10.1007/3-540-45105-6_39

Genetic and Evolutionary Computation - GECCO 2003 : Genetic and Evolutionary Computation Conference, Chicago, IL, USA, July 12-16, 2003 : Proceedings, Part I

Genetic and Evolutionary Computation GECCO 2003, 12-16.07.2003, Chicago, United States