GP算法在图像分析上的应用综述
A Survey on Genetic Programming to Image Analysis

GP（Genetic Programming）算法，常被称为遗传规划、遗传编程或遗传程序设计，是一种进化计算算法能够利用计算机技术自动生成“程序”（模型）解决实际问题。介绍了GP算法基本原理、算法目前发展及其主要应用领域。对GP算法在图象分析领域和特征提取、图像分类、边缘检测、图像分割等的代表性研究工作进行了较为系统且全面的讨论和综述。最后，对GP算法在图像分析上的研究难点及热点如计算复杂、提高泛化能力、迁移学习等进行了总结和归纳，指出了未来主要研究方向。
As an evolutionary computation (EC) technique, Genetic programming (GP) has been widely applied to image analysis in recent decades. However, there was no comprehensive and systematic literature review in this area. To provide guidelines for the state-of-the-art research, this paper presented a survey of the literature in recent years on GP for image analysis, including feature extraction, image classification, edge detection, and image segmentation. In addition, this paper summarised the current issues and challenges, such as computationally expensive, generalisation ability and transfer learning, on GP forimage analysis, and pointd out promising research directions for future work.