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Advanced machine learning techniques for computer vision

  • Part 3: Machine Learning
  • Conference paper
  • First Online:
Advanced Topics in Artificial Intelligence

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 617))

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Abstract

Learning is a critical research field for autonomous computer vision systems. It can bring solutions to the knowledge acquisition bottleneck of image understanding systems. Recent developments of machine learning for computer vision are reported in this paper. We describe several different approaches for learning at different levels of the image understanding process, including learning 2-D shape models, learning strategic knowledge for optimizing model matching, learning for adaptative target recognition systems, knowledge acquisition of constraint rules for labelling and automatic parameter optimization for vision systems.

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Authors and Affiliations

  1. CNRS & Université Paris Sud, LRI, Bat 490, F-91405, Orsay, France

    S. Moscatelli & Y. Kodratoff

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  1. S. Moscatelli
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  2. Y. Kodratoff
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Vladimír Mřrík Olga Štěpánková Rorbert Trappl

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© 1992 Springer-Verlag Berlin Heidelberg

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Moscatelli, S., Kodratoff, Y. (1992). Advanced machine learning techniques for computer vision. In: Mřrík, V., Štěpánková, O., Trappl, R. (eds) Advanced Topics in Artificial Intelligence. Lecture Notes in Computer Science, vol 617. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-55681-8_35

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  • DOI: https://doi.org/10.1007/3-540-55681-8_35

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-55681-7

  • Online ISBN: 978-3-540-47271-1

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