Coevolutionary Computation for Synthesis of Recognition Systems
This paper introduces a novel visual learning method that involves cooperative coevolution and linear genetic programming. Given exclusively training images, the evolutionary learning algorithm induces a set of sophisticated feature extraction agents represented in a procedural way. The proposed method incorporates only general vision-related background knowledge and does not require any task-specific information. The paper describes the learning algorithm, provides a firm rationale for its design, and proves its competitiveness with the human-designed recognition systems in an extensive experimental evaluation, on the demanding real-world task of object recognition in synthetic aperture radar (SAR) imagery.