- author = "Wenlong Fu and Mark Johnston and Mengjie Zhang",
- title = "Genetic programming for edge detection based on figure of merit",
- booktitle = "GECCO Companion '12: Proceedings of the fourteenth international conference on Genetic and evolutionary computation conference companion",
- year = "2012",
- editor = "Terry Soule and Anne Auger and Jason Moore and David Pelta and Christine Solnon and Mike Preuss and Alan Dorin and Yew-Soon Ong and Christian Blum and Dario Landa Silva and Frank Neumann and Tina Yu and Aniko Ekart and Will Browne and Tim Kovacs and Man-Leung Wong and Clara Pizzuti and Jon Rowe and Tobias Friedrich and Giovanni Squillero and Nicolas Bredeche and Stephen L. Smith and Alison Motsinger-Reif and Jose Lozano and Martin Pelikan and Silja Meyer-Nienberg and Christian Igel and Greg Hornby and Rene Doursat and Steve Gustafson and Gustavo Olague and Shin Yoo and John Clark and Gabriela Ochoa and Gisele Pappa and Fernando Lobo and Daniel Tauritz and Jurgen Branke and Kalyanmoy Deb",
- isbn13 = "978-1-4503-1178-6",
- keywords = "genetic algorithms, Genetic programming: Poster",
- pages = "1483--1484",
- month = "7-11 " # jul,
- organisation = "SIGEVO",
- address = "Philadelphia, Pennsylvania, USA",
-
DOI = "
doi:10.1145/2330784.2331003",
- publisher = "ACM",
- publisher_address = "New York, NY, USA",
- abstract = "The figure of merit (FOM) is popular for testing an edge detector's performance, but there are very few reports using FOM as an evaluation method in the learning stage of supervised learning methods. In this study, FOM is investigated as a fitness function in Genetic Programming (GP) for edge detection. Since FOM has some drawbacks from type II errors, new fitness functions are developed based on FOM in order to address these weaknesses. Experimental results show that FOM can be used to evolve GP edge detectors that perform better than the Sobel detector, and the new fitness functions clearly improve the ability of GP edge detectors to find edge points and give a single response on edges, compared with the fitness function using FOM.",
-
notes = "Also known as \cite{2331003} Distributed at
GECCO-2012.
ACM Order Number 910122.",
