Exploring genetic programming in image processing: Challenges and enhanced techniques
學年 113
學期 1
發表日期 2025-01-03
作品名稱 Exploring genetic programming in image processing: Challenges and enhanced techniques
作品名稱（其他語言）
著者 Chang, Feng-cheng; Huang, Hsiang-cheh
作品所屬單位
出版者
會議名稱 2025 19th International Conference on Ubiquitous Information Management and Communication (IMCOM)
會議地點 Bangkok, Thailand
摘要 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 optimizing GP in future applications.
關鍵字 Training;Refining;Neural networks;Genetic programming;Transformers;Image filtering;Information management;Reliability;Optimization;Convergence
語言 en_US
收錄於
會議性質 國際
校內研討會地點 無
研討會時間 20250103~20250105
通訊作者
國別 THA
公開徵稿
出版型式
出處 2025 19th International Conference on Ubiquitous Information Management and Communication (IMCOM)
SDGS 優質教育,產業創新與基礎設施