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Evolutionary Synthesis of Pattern Recognition Systems

Designing object detection and recognition systems that work in the real world is a challenging task due to various factors including the high complexity of the systems, the dynamically changing environment of the real world and factors such as occlusion, clutter, articulation, and various noise con...

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Bibliographic Details
Main Authors: Bhanu, Bir. (Author, http://id.loc.gov/vocabulary/relators/aut), Lin, Yingqiang. (http://id.loc.gov/vocabulary/relators/aut), Krawiec, Krzysztof. (http://id.loc.gov/vocabulary/relators/aut)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:English
Published: New York, NY : Springer New York : Imprint: Springer, 2005.
Edition:1st ed. 2005.
Series:Monographs in Computer Science,
Subjects:
Pattern recognition.
Optical data processing.
Artificial intelligence.
User interfaces (Computer systems).
Computers.
Pattern Recognition.
Computer Imaging, Vision, Pattern Recognition and Graphics.
Image Processing and Computer Vision.
Artificial Intelligence.
User Interfaces and Human Computer Interaction.
Computation by Abstract Devices.
Online Access:https://doi.org/10.1007/b105515
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Table of Contents:
  • Feature Synthesis for Object Detection
  • Mdl-Based Efficient Genetic Programming for Object Detection
  • Feature Selection for Object Detection
  • Evolutionary Feature Synthesis for Object Recognition
  • Linear Genetic Programming for Object Recognition
  • Applications of Linear Genetic Programming for Object Recognition
  • Summary and Future Work.

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