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Filters for graph-based keyword spotting in historical handwritten documents

  • Published:2020-06 Issue: Volume:134 Page:125-134
  • ISSN:0167-8655
  • Container-title:Pattern Recognition Letters
  • language:en
  • Short-container-title:Pattern Recognition Letters

Author:

Stauffer MichaelORCID,Fischer Andreas,Riesen Kaspar

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference50 articles.

1. Keyword spotting in poorly printed documents using pseudo 2-d hidden markov models;Kuo;IEEE Trans. Pattern Anal. Mach. Intell.,1994

2. Word spotting and recognition with embedded attributes;Almazán;IEEE Trans. Pattern Anal. Mach. Intell.,2014

3. Keyword spotting in historical documents based on handwriting graphs and hausdorff edit distance;Ameri,2017

4. Efficient matching and indexing of graph models in content-based retrieval;Berretti;IEEE Trans. Pattern Anal. Mach. Intell.,2001

5. Unsupervised word spotting using a graph representation based on invariants;Bui,2015

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1. A novel multi-task learning technique for offline handwritten short answer spotting and recognition;Multimedia Tools and Applications;2023-11-20

2. A novel optimized deep learning framework to spot keywords and query matching process in Devanagari scripts;Multimedia Tools and Applications;2023-03-01

3. Z-Transform-Based Profile Matching to Develop a Learning-Free Keyword Spotting Method for Handwritten Document Images;International Journal of Computational Intelligence Systems;2022-11-02

4. Multivalent Graph Matching for Symbol Recognition;Document Analysis and Recognition – ICDAR 2021 Workshops;2021

5. A Semantic Search Engine for Historical Handwritten Document Images;Linking Theory and Practice of Digital Libraries;2021
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