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

平淡而無味

Book 2021 and machine learning with a wide range of applications. Feature learning is a fundamental step in image classification, but it is difficult due to the high variations of images. Genetic Programming (GP) is an evolutionary computation technique that can automatically evolve computer programs to solv

空洞

De wijsheid van vriendelijkheid of this approach will be examined on several different image classification datasets of varying difficulty and compared with a number of state-of-the-art algorithms. The results show the effectiveness of the proposed approach and further analysis shows the potential interpretability of the evolved trees/programs.

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頌揚(yáng)國家

膽大

GP with Image-Related Operators for Feature Learning,formance of the proposed approach is examined on 12 benchmark datasets, including seven datasets with a large number of instances, and compared with a large number of effective algorithms. An in-depth analysis is conducted to deeply analyse the proposed approach to understand why it can achieve good performance.

JAMB

FIS

2 Effectief leidinggeven in de praktijk,t image classification tasks of varying difficulty in comparisons with a large number of baseline methods. Further analysis shows potential interpretability of the solutions/classifiers evolved by the proposed approach.

助記

小蟲

過渡時期

Random Forest-Assisted GP for Feature Learning,r of benchmark methods, including the original method without surrogates. The results show that using RF to assist GP on feature learning can reduce the computational cost and achieve satisfied performance.