Titlebook: Genetic Programming for Image Classification; An Automated Approac Ying Bi,Bing Xue,Mengjie Zhang Book 2021 The Editor(s) (if applicable) a

Entangle

書目名稱Genetic Programming for Image Classification影響因子(影響力)




書目名稱Genetic Programming for Image Classification影響因子(影響力)學科排名




書目名稱Genetic Programming for Image Classification網(wǎng)絡公開度




書目名稱Genetic Programming for Image Classification網(wǎng)絡公開度學科排名




書目名稱Genetic Programming for Image Classification被引頻次




書目名稱Genetic Programming for Image Classification被引頻次學科排名




書目名稱Genetic Programming for Image Classification年度引用




書目名稱Genetic Programming for Image Classification年度引用學科排名




書目名稱Genetic Programming for Image Classification讀者反饋




書目名稱Genetic Programming for Image Classification讀者反饋學科排名

集中營

Evolutionary Computation and Genetic Programming, describes the basics of genetic programming, including representation, functions, terminals, population initialisation, genetic operators, and strongly typed genetic programming, in detail. Finally, it reviews typical works on genetic programming for feature learning.

SCORE

諄諄教誨

向外

GP with Image Descriptors for Learning Global and Local Features,ariations. These image descriptors can be used to extract two types of image features, i.e., global features and local features. But domain expertise is often needed to determine what features are extracted. This chapter proposes a new feature learning approach using GP to automatically select and c

Infant

GP with Image-Related Operators for Feature Learning,fective feature learning. However, this has not been extensively investigated in GP due to the limitations of the current GP representations. This chapter proposes a new GP-based approach with a flexible program structure and a number of image-related operators for feature learning in image classifi

Infant

GP for Simultaneous Feature Learning and Ensemble Learning,assification often need many manually settings and extensive human intervention on feature extraction, base learner selection and combination. Automating the processes of feature extraction and ensemble building can address this issue. This chapter proposes a GP-based approach with a new representat

arsenal

JUST

https://doi.org/10.1007/978-3-030-65927-1Evolutionary Computation; Genetic Programming; Feature Learning; Image Classification; Computer Vision; M

謊言

Dick Mul,Ingrid Bliek,Katja ZuurThis chapter provides a summary of the book. This chapter revisits the main GP-based approaches presented in the book and summaries the major conclusions. It also highlights several key research directions to encourage future work.