Refining Fitness Functions and Optimising Training Data in GP for Object Detection

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@InProceedings{DBLP:conf/seal/ZhangLM06,

• author = "Mengjie Zhang and Malcolm Lett and Yuejin Ma",
• title = "Refining Fitness Functions and Optimising Training Data in GP for Object Detection",
• booktitle = "Simulated Evolution and Learning, Proceedings 6th International Conference, SEAL 2006",
• year = "2006",
• pages = "601--608",
• DOI = "doi:10.1007/11903697_76",
• bibsource = "DBLP, http://dblp.uni-trier.de",
• editor = "Tzai-Der Wang and Xiaodong Li and Shu-Heng Chen and Xufa Wang and Hussein A. Abbass and Hitoshi Iba and Guoliang Chen and Xin Yao",
• publisher = "Springer",
• series = "Lecture Notes in Computer Science",
• volume = "4247",
• ISBN = "3-540-47331-9",
• address = "Hefei, China",
• month = oct # " 15-18",
• keywords = "genetic algorithms, genetic programming",
• abstract = "This paper describes an approach to the refinement of a fitness function and the optimisation of training data in genetic programming for object detection particularly object localisation problems. The approach is examined and compared with an existing fitness function on three object detection problems of increasing difficulty. The results suggest that the new fitness function outperforms the old one by producing far fewer false alarms and spending much less training time and that some particular types of training examples contain most of the useful information for object detection.",

}

Genetic Programming entries for Mengjie Zhang Malcolm Lett Yuejin Ma

Citations