%0 Conference Paper %1 LettZhang:04:ivcnz %A Lett, Malcolm %A Zhang, Mengjie %B Proceeding of Image and Vision Computing International Conference %C Akaroa, New Zealand %D 2004 %E Pairman, David %E North, Heather %E McNeill, Stephen %I Lincoln, Landcare Research %K algorithms, detection, fitness function genetic localisation, object programming, %P 441--446 %T New Fitness Functions in Genetic Programming for Object Detection %X Object detection is an important field of research in computer vision which genetic programming has been applied to recently. This paper describes two new fitness functions in genetic programming for object detection. Both fitness functions are based on recall and precision of genetic programs. The first is a tolerance based fitness function and the second is a weighted fitness function. The merits and effectiveness of the two fitness function are discussed. The two fitness functions are examined and compared on three object detection problems of increasing dificulty. The results suggest that both fitness functions perform very well on the relatively easy problem, the weighted fitness function outperforms the tolerance based fitness function on the relatively dificult problems.

@inproceedings{LettZhang:04:ivcnz, abstract = {Object detection is an important field of research in computer vision which genetic programming has been applied to recently. This paper describes two new fitness functions in genetic programming for object detection. Both fitness functions are based on recall and precision of genetic programs. The first is a tolerance based fitness function and the second is a weighted fitness function. The merits and effectiveness of the two fitness function are discussed. The two fitness functions are examined and compared on three object detection problems of increasing dificulty. The results suggest that both fitness functions perform very well on the relatively easy problem, the weighted fitness function outperforms the tolerance based fitness function on the relatively dificult problems.}, added-at = {2008-06-19T17:35:00.000+0200}, address = {Akaroa, New Zealand}, author = {Lett, Malcolm and Zhang, Mengjie}, biburl = {https://www.bibsonomy.org/bibtex/23e38685fd4176b5f6f7e35a1d02cc6d7/brazovayeye}, booktitle = {Proceeding of Image and Vision Computing International Conference}, editor = {Pairman, David and North, Heather and McNeill, Stephen}, interhash = {a0ac0e9bc448d1c41039ef8cd39a0511}, intrahash = {3e38685fd4176b5f6f7e35a1d02cc6d7}, keywords = {algorithms, detection, fitness function genetic localisation, object programming,}, month = {November}, notes = {Fri, 02 Jun 2006 17:03:20 +0800 IVCNZ}, pages = {441--446}, publisher = {Lincoln, Landcare Research}, size = {6 pages}, timestamp = {2008-06-19T17:45:25.000+0200}, title = {New Fitness Functions in Genetic Programming for Object Detection}, year = 2004 }