- author = "Feng-Cheng Chang and Hsiang-Cheh Huang",
- title = "Exploring Genetic Programming in Image Processing: Challenges and Enhanced Techniques",
- booktitle = "2025 19th International Conference on Ubiquitous Information Management and Communication (IMCOM)",
- year = "2025",
- month = jan,
- keywords = "genetic algorithms, genetic programming, Training, Refining, Neural networks, Transformers, Image filtering, Information management, Reliability, Optimisation, Convergence, symbolic transformer",
-
DOI = "
doi:10.1109/IMCOM64595.2025.10857586",
- abstract = "In recent years, the advancement of AI has been primarily driven by neural networks, which, despite their success, pose challenges in terms of explainability and high-power consumption. Genetic Programming (GP) offers an interpretable alternative, although its complexity has limited its practical application. This paper explores the potential of GP through experiments on a simple image filtering task, aiming to understand its properties and limitations. We also investigate the integration of transformer concepts into the GP process. Preliminary results suggest that while GP faces convergence challenges, the introduction of symbolic transformers may enhance its effectiveness in image processing tasks. These findings open up new possibilities for optimising GP in future applications.",
-
notes = "Also known as \cite{10857586}
Tamkang University, Taiwan, R.O.C",
