Machine Learning in Document Analysis and Recognition 2008

• Simone Marinai:
  Introduction to Document Analysis and Recognition. 1-20
  
• Abdel Belaïd, Yves Rangoni:
  Structure Extraction in Printed Documents Using Neural Approaches. 21-43
  
• Donato Malerba, Michelangelo Ceci, Margherita Berardi:
  Machine Learning for Reading Order Detection in Document Image Understanding. 45-69
  
• Richard Zanibbi, Dorothea Blostein, James R. Cordy:
  Decision-Based Specification and Comparison of Table Recognition Algorithms. 71-103
  
• Floriana Esposito, Stefano Ferilli, Teresa Maria Altomare Basile, Nicola Di Mauro:
  Machine Learning for Digital Document Processing: from Layout Analysis to Metadata Extraction. 105-138
  
• Cheng-Lin Liu, Hiromichi Fujisawa:
  Classification and Learning Methods for Character Recognition: Advances and Remaining Problems. 139-161
  
• Stefan Jaeger, Huanfeng Ma, David S. Doermann:
  Combining Classifiers with Informational Confidence. 163-191
  
• Simone Marinai, Emanuele Marino, Giovanni Soda:
  Self-Organizing Maps for Clustering in Document Image Analysis. 193-219
  
• George Nagy, Sriharsha Veeramachaneni:
  Adaptive and Interactive Approaches to Document Analysis. 221-257
  
• Michael Blumenstein:
  Cursive Character Segmentation Using Neural Network Techniques. 259-275
  
• Tatsuhiko Kagehiro, Hiromichi Fujisawa:
  Multiple Hypotheses Document Analysis. 277-303
  
• Sergey Tulyakov, Venu Govindaraju:
  Learning Matching Score Dependencies for Classifier Combination. 305-332
  
• Tamás Varga, Horst Bunke:
  Perturbation Models for Generating Synthetic Training Data in Handwriting Recognition. 333-360
  
• Sergey Tulyakov, Stefan Jaeger, Venu Govindaraju, David S. Doermann:
  Review of Classifier Combination Methods. 361-386
  
• Sargur N. Srihari, Harish Srinivasan, Siyuan Chen, Matthew J. Beal:
  Machine Learning for Signature Verification. 387-408
  
• Andreas Schlapbach, Horst Bunke:
  Off-line Writer Identification and Verification Using Gaussian Mixture Models. 409-428