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In computer vision and machine learning, image classification is an important and fundamental task, which assigns images to one of pre-defined groups based on the content in the images. It has a wide range of applications in various fields, such as medicine, biology, remote-sensing, and engineering. Image classification is also a key component of many other visual tasks, such as object detection, video annotation, and image retrieval. However, image classification is a challenging task due to high variations of background, illumination, viewpoint, scale, deformation, and occlusion across images
Introduction
Computer Vision and Machine Learning
Evolutionary Computation and Genetic Programming
Multi-layer Representation for Binary Image Classification
Evolutionary Deep Learning Using GP with Convolution Operators
GP with Image Descriptors for Learning Global and Local Features
GP with Image-Related Operators for Feature Learning
GP for Simultaneous Feature Learning and Ensemble Learning
Random Forest-Assisted GP for Feature Learning
Conclusions and Future Directions
Appendix: Implementation Instructions