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Pattern Recognition and Machine Intelligence

4th International Conference, PReMI 2011, Moscow, Russia, June 27 - July 1, 2011, Proceedings

  • Conference proceedings
  • © 2011

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Editors:
  1. Sergei O. Kuznetsov

    1. State University Higher School of Economics, Moscow, Russia

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  2. Deba P. Mandal

    1. Machine Intelligence Unit, Indian Statistical Institute, Kolkata, India

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  3. Malay K. Kundu

    1. Machine Intelligence, Indian Statistical Institute, Kolkata, India

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  4. Sankar K. Pal

    1. Machine Intelligence, Indian Statistical Institute, Kolkata, India

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 6744)

Part of the book sub series: Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)

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Conference proceedings info: PReMI 2011.

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About this book

This book constitutes the refereed proceedings of the 4th International Conference on Pattern Recognition and Machine Intelligence, PReMI 2011, held in Moscow, Russia in June/July 2011. The 65 revised papers presented together with 5 invited talks were carefully reviewed and selected from 140 submissions. The papers are organized in topical sections on pattern recognition and machine learning; image analysis; image and video information retrieval; natural language processing and text and data mining; watermarking, steganography and biometrics; soft computing and applications; clustering and network analysis; bio and chemo analysis; and document image processing.

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Table of contents (76 papers)

  1. Front Matter

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  2. Invited Talks

    1. Enriching Education through Data Mining

      • Rakesh Agrawal, Sreenivas Gollapudi, Anitha Kannan, Krishnaram Kenthapadi
      Pages 1-2

    2. How to Visualize a Crisp or Fuzzy Topic Set over a Taxonomy

      • Boris Mirkin, Susana Nascimento, Trevor Fenner, Rui Felizardo
      Pages 3-12

    3. On Merging the Fields of Neural Networks and Adaptive Data Structures to Yield New Pattern Recognition Methodologies

      • B. John Oommen
      Pages 13-16

    4. Quality of Algorithms for Sequence Comparison

      • Mikhail Roytberg
      Pages 17-20

    5. Problems of Machine Learning

      • Alexei Ya. Chervonenkis
      Pages 21-23

  3. Pattern Recognition and Machine Learning

    1. Bayesian Approach to the Pattern Recognition Problem in Nonstationary Environment

      • O. V. Krasotkina, V. V. Mottl, P. A. Turkov
      Pages 24-29

    2. The Classification of Noisy Sequences Generated by Similar HMMs

      • A. A. Popov, T. A. Gultyaeva
      Pages 30-35

    3. NDoT: Nearest Neighbor Distance Based Outlier Detection Technique

      • Neminath Hubballi, Bidyut Kr. Patra, Sukumar Nandi
      Pages 36-42

    4. Some Remarks on the Relation between Annotated Ordered Sets and Pattern Structures

      • Tim B. Kaiser, Stefan E. Schmidt
      Pages 43-48

    5. Solving the Structure-Property Problem Using k-NN Classification

      • Aleksandr Perevoznikov, Alexey Shestov, Evgenii Permiakov, Mikhail Kumskov
      Pages 49-53

    6. Stable Feature Extraction with the Help of Stochastic Information Measure

      • Alexander Lepskiy
      Pages 54-59

    7. Wavelet-Based Clustering of Social-Network Users Using Temporal and Activity Profiles

      • Lipika Dey, Bhakti Gaonkar
      Pages 60-65

    8. Tight Combinatorial Generalization Bounds for Threshold Conjunction Rules

      • Konstantin Vorontsov, Andrey Ivahnenko
      Pages 66-73

    9. An Improvement of Dissimilarity-Based Classifications Using SIFT Algorithm

      • Evensen E. Masaki, Sang-Woon Kim
      Pages 74-79

    10. Introduction, Elimination Rules for ¬ and ⊃: A Study from Graded Context

      • Soma Dutta
      Pages 80-85
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  1. Pattern Recognition and Machine Intelligence

Editors and Affiliations

  • State University Higher School of Economics, Moscow, Russia

    Sergei O. Kuznetsov

  • Machine Intelligence Unit, Indian Statistical Institute, Kolkata, India

    Deba P. Mandal

  • Machine Intelligence, Indian Statistical Institute, Kolkata, India

    Malay K. Kundu, Sankar K. Pal

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