- author = "Mengjie Zhang",
- title = "A Domain Independent Approach to {2D} Object Detection Based on the Neural and Genetic Paradigms",
- school = "Department of Computer Science, RMIT University",
- year = "2000",
- address = "Melbourne, Victoria, Australia",
- month = aug,
- keywords = "genetic algorithms, genetic programming, ANN, computer vision",
-
URL = "
http://www.mcs.vuw.ac.nz/~mengjie/papers/mengjie-thesis.pdf",
-
URL = "http://goanna.cs.rmit.edu.au/~vc/papers/zhang-phd.pdf",
-
URL = "
http://citeseer.ist.psu.edu/zhang00domain.html",
- size = "255 pages",
-
abstract = "The development of traditional object detection
systems usually involves a time consuming investigation
of good preprocessing and filtering methods and a
hand-crafting of different programs for the extraction
and selection of important image features in different
problem domains. To avoid these problems, this thesis
describes a domain independent approach to multiple
class, translation and rotation invariant object
detection problems without any preprocessing,
segmentation and specific feature extraction. The
approach is based on learning/adaptive methods --
neural networks, genetic algorithms and genetic
programming. Rather than using...
6th 'a method which uses genetic programming to build the object detector'. Retina images.",
-
notes = "
Supervisors: Victor Ciesielski and James Thom",
