- author = "Mengjie Zhang and Victor B. Ciesielski and Peter Andreae",
- title = "A Domain-independent Window approach to Multiclass Object Detection using Genetic Programming",
- journal = "{EURASIP} Journal on Applied Signal Processing",
- year = "2003",
- volume = "2003",
- number = "8",
- pages = "841--859",
- month = jul,
- note = "Special Issue on Genetic and Evolutionary Computation for Signal Processing and Image Analysis",
- email = "mengjie@mcs.vuw.ac.nz",
- keywords = "genetic algorithms, genetic programming, machine learning, neural networks, object recognition, target detection, computer vision",
- ISSN = "1110-8657",
-
URL = "
http://www.mcs.vuw.ac.nz/~pondy/eurasip2003.pdf",
-
URL = "http://downloads.hindawi.com/journals/asp/2003/206791.pdf",
-
DOI = "
10.1155/S1110865703303063",
- abstract = "a domain-independent approach to the use of genetic programming for object detection problems in which the locations of small objects of multiple classes in large images must be found. The evolved program is scanned over the large images to locate the objects of interest. The paper develops three terminal sets based on domain-independent pixel statistics and considers two different function sets. The fitness function is based on the detection rate and the false alarm rate. We have tested the method on three object detection problems of increasing difficulty. This work not only extends genetic programming to multiclass-object detection problems, but also shows how to use a single evolved genetic program for both object classification and localisation. The object classification map developed in this approach can be used as a general classification strategy in genetic programming for multiple-class classification problems.",
-
notes = "Special Issue on genetic and evolutionary computation
for signal processing and image analysis
http://asp.hindawi.com/volume-2003/issue-8.html
European Association for Speech, Signal and Image
Processing (EURASIP) asp@asp.hindawi.com
31 Aug 2003 problems reading PDF",
