- author = "Malcolm Lett",
- title = "Improving Training Performance of Genetic Programming for Object Detection",
- howpublished = "Undergraduate project",
- school = "Computer Science, Victoria University of Wellington",
- year = "2004",
- address = "Wellington, New Zealand",
- month = oct # " 23",
- keywords = "genetic algorithms, genetic programming",
-
URL = "
http://homepages.ecs.vuw.ac.nz/~mengjie/students/malcolm.pdf",
- size = "66 pages",
- abstract = "Object detection has become an important research topic within computer science. Databases of images need to be searched, security images and speed camera images need image processing to search for various information, and there is an increased desire that computers should be able to recognise human faces and determine who they are. Genetic programming has been used for these sorts of tasks with varying success, however object detection is still a difficult task and can require long training times. This project investigates the task of finding the accurate positions of objects. From this investigation, two new fitness functions are devised which are competitive with existing methods in terms of detection rate, false alarm rate and time to evolve the solution programs when applied to data sets of increasing difficulty. Also produced from this investigation are guidelines for the types of data which should be trained on for object detection.",
-
notes = "Submitted in partial fulfilment of the requirements
for Bachelor of Science with Honours in Computer
Science.
Supervisor: Dr. Mengjie Zhang",
