A New Genetic Programming Representation for Feature Learning in Skin Cancer Detection

Abstract

The process of automatically extracting informative high-level features from skin cancer images is enhanced by integrating well-developed feature descriptors into learning algorithms. This paper develops a new genetic programming-based feature learning approach to automatically select and combine six well-developed descriptors to extract high-level features for skin cancer image classification. The new approach can automatically learn various global features for image classification. The experimental results show that the new approach achieves significantly better classification performance than the baseline approach and six commonly used feature descriptors on two real-world skin image datasets.