research-article

Cross-Domain Reuse of Extracted Knowledge in Genetic Programming for Image Classification

Authors:

Muhammad Iqbal,

Harith Al-Sahaf,

Mengjie ZhangAuthors Info & Claims

IEEE Transactions on Evolutionary Computation, Volume 21, Issue 4

Pages 569 - 587

https://doi.org/10.1109/TEVC.2017.2657556

Published: 01 August 2017 Publication History

Abstract

Genetic programming (GP) is a well-known evolutionary computation technique, which has been successfully used to solve various problems, such as optimization, image analysis, and classification. Transfer learning is a type of machine learning approach that can be used to solve complex tasks. Transfer learning has been introduced to GP to solve complex Boolean and symbolic regression problems with some promise. However, the use of transfer learning with GP has not been investigated to address complex image classification tasks with noise and rotations, where GP cannot achieve satisfactory performance, but GP with transfer learning may improve the performance. In this paper, we propose a novel approach based on transfer learning and GP to solve complex image classification problems by extracting and reusing blocks of knowledge/information, which are automatically discovered from similar as well as different image classification tasks during the evolutionary process. The proposed approach is evaluated on three texture data sets and three office data sets of image classification benchmarks, and achieves better classification performance than the state-of-the-art image classification algorithm. Further analysis on the evolved solutions/trees shows that the proposed approach with transfer learning can successfully discover and reuse knowledge/information extracted from similar or different problems to improve its performance on complex image classification problems.

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Banzhaf WBakurov ILi XHandl J(2024)On the Nature of the Phenotype in Tree Genetic ProgrammingProceedings of the Genetic and Evolutionary Computation Conference10.1145/3638529.3654129(868-877)Online publication date: 14-Jul-2024
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Index Terms

Cross-Domain Reuse of Extracted Knowledge in Genetic Programming for Image Classification
1. Computing methodologies
  1. Artificial intelligence
    1. Search methodologies
  2. Machine learning
    1. Learning paradigms
      1. Supervised learning
    2. Machine learning approaches

Index terms have been assigned to the content through auto-classification.

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cover image IEEE Transactions on Evolutionary Computation

IEEE Transactions on Evolutionary Computation Volume 21, Issue 4

Aug. 2017

168 pages

ISSN:1089-778X

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Masood ZJiangbin ZAhmad IDongdong CShabbir WIrfan M(2024)A novel continual reinforcement learning-based expert system for self-optimization of soft real-time systemsExpert Systems with Applications: An International Journal10.1016/j.eswa.2023.122309238:PEOnline publication date: 27-Feb-2024
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