%0 Thesis %1 mengjie-thesis %A Zhang, Mengjie %C Melbourne, Victoria, Australia %D 2000 %K ANN, algorithms, computer genetic programming, vision %T A Domain Independent Approach to 2D Object Detection Based on the Neural and Genetic Paradigms %U http://citeseer.ist.psu.edu/zhang00domain.html %X 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.

@phdthesis{mengjie-thesis, 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.}, added-at = {2008-06-19T17:46:40.000+0200}, address = {Melbourne, Victoria, Australia}, author = {Zhang, Mengjie}, biburl = {https://www.bibsonomy.org/bibtex/2db5de3af6491f85e4c808cd785959612/brazovayeye}, interhash = {21ce9d34ad4826a1ba9c8f3bf5fae6c5}, intrahash = {db5de3af6491f85e4c808cd785959612}, keywords = {ANN, algorithms, computer genetic programming, vision}, month = {August}, school = {Department of Computer Science, RMIT University}, size = {225 pages}, timestamp = {2008-06-19T17:55:31.000+0200}, title = {A Domain Independent Approach to 2{D} Object Detection Based on the Neural and Genetic Paradigms}, url = {http://citeseer.ist.psu.edu/zhang00domain.html}, year = 2000 }