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Model Development and Incremental Learning Based on Case-Based Reasoning for Signal and Image Analysis

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Computational Modeling of Objects Presented in Images. Fundamentals, Methods, and Applications (CompIMAGE 2016)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10149))

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Abstract

Over the years, image mining and knowledge discovery gained importance to solving problems. They are used in developing systems for automatic signal analysis and interpretation. The issues of model building and adaption, allowing an automatic system to adjust to the changing environments and moving objects, became increasingly important. One method of achieving adaptation in model building and model learning is Case-Based Reasoning (CBR). Case-Based Reasoning can be seen as a reasoning method as well as an incremental learning and knowledge acquisition method. In this paper we provide an overview of the CBR process and its main features: similarity, memory organization, CBR learning, and case-base maintenance. Then we review, based on applications, what has been achieved so far. The applications we are focusing on are meta-learning for parameter selection, image interpretation, incremental prototype-based classification, novelty detection and handling, and 1-D signal interpretation represented by a 0_1 sequence. Finally, we will summarize the overall concept of CBR usage for model development and learning.

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Authors and Affiliations

  1. Institute of Computer Vision and Applied Computer Sciences, IBaI, Leipzig, Germany

    Petra Perner

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  1. Petra Perner
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Correspondence to Petra Perner .

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Editors and Affiliations

  1. State University of New York at Fredonia , Fredonia, New York, USA

    Reneta P. Barneva

  2. State University of New York , Buffalo, New York, USA

    Valentin E. Brimkov

  3. Universidade do Porto , Porto, Portugal

    João Manuel R.S. Tavares

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Perner, P. (2017). Model Development and Incremental Learning Based on Case-Based Reasoning for Signal and Image Analysis. In: Barneva, R., Brimkov, V., Tavares, J. (eds) Computational Modeling of Objects Presented in Images. Fundamentals, Methods, and Applications. CompIMAGE 2016. Lecture Notes in Computer Science(), vol 10149. Springer, Cham. https://doi.org/10.1007/978-3-319-54609-4_1

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