- author = "Krzysztof Krawiec and Mateusz Nawrocki",
- title = "Implicit Fitness Sharing for Evolutionary Synthesis of License Plate Detectors",
- booktitle = "Applications of Evolutionary Computing, EvoApplications 2012: EvoCOMNET, EvoCOMPLEX, EvoENERGY, EvoFIN, EvoGAMES, EvoIASP, EvoINDUSTRY, EvoNUM, EvoPAR, EvoRISK, EvoROBOT, EvoSTOC",
- year = "2013",
- editor = "Anna I. Esparcia-Alcazar and Antonio Della Cioppa and Ivanoe {De Falco} and Ernesto Tarantino and Carlos Cotta and Robert Schaefer and Konrad Diwold and Kyrre Glette and Andrea Tettamanzi and Alexandros Agapitos and Paolo Burrelli and J. J. Merelo and Stefano Cagnoni and Mengjie Zhang and Neil Urquhart and Kevin Sim and Aniko Ekart and Francisco {Fernandez de Vega} and Sara Silva and Evert Haasdijk and Gusz Eiben and Anabela Simoes and Philipp Rohlfshagen",
- volume = "7835",
- series = "Lecture Notes in Computer Science",
- pages = "376--386",
- address = "Vienna, Austria",
- publisher_address = "Berlin",
- month = "3-5 " # apr,
- organisation = "EvoStar",
- publisher = "Springer",
- keywords = "genetic algorithms, genetic programming, pattern recognition, image analysis, implicit fitness sharing, car number plate recognition",
- isbn13 = "978-3-642-37191-2",
-
DOI = "
doi:10.1007/978-3-642-37192-9_38",
- size = "11 pages",
- abstract = "A genetic programming algorithm for synthesis of object detection systems is proposed and applied to the task of license plate recognition in uncontrolled lighting conditions. The method evolves solutions represented as data flows of high-level parametric image operators. In an extended variant, the algorithm employs implicit fitness sharing, which allows identifying the particularly difficult training examples and focusing the training process on them. The experiment, involving heterogeneous video sequences acquired in diverse conditions, demonstrates that implicit fitness sharing substantially improves the predictive performance of evolved detection systems, providing maximum recognition accuracy achievable for the considered setup and training data.",
-
notes = "
EvoApplications2013 held in conjunction with EuroGP2013, EvoCOP2013, EvoBio'2013 and EvoMusArt2013",
