A machine learning based approach for table detection on the web
Proceedings of the 11th international conference on World Wide Web
Recognizing records from the extracted cells of microfilm tables
Proceedings of the 2002 ACM symposium on Document engineering
Issues in Ground-Truthing Graphic Documents
GREC '01 Selected Papers from the Fourth International Workshop on Graphics Recognition Algorithms and Applications
Configuration REcognition Model for Complex Reverse Engineering Methods: 2(CREM)
DAS '02 Proceedings of the 5th International Workshop on Document Analysis Systems V
Arabic Newspaper Page Segmentation
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
Automating the extraction of data from HTML tables with unknown structure
Data & Knowledge Engineering - Special issue: ER 2002
Transforming arbitrary tables into logical form with TARTAR
Data & Knowledge Engineering
A composite approach to automating direct and indirect schema mappings
Information Systems
Towards domain-independent information extraction from web tables
Proceedings of the 16th international conference on World Wide Web
Tools for monitoring, visualizing, and refining collections of noisy documents
Proceedings of The Third Workshop on Analytics for Noisy Unstructured Text Data
From Tessellations to Table Interpretation
Calculemus '09/MKM '09 Proceedings of the 16th Symposium, 8th International Conference. Held as Part of CICM '09 on Intelligent Computer Mathematics
Fast Compressed Domain Motion Detection in H.264 Video Streams for Video Surveillance Applications
AVSS '09 Proceedings of the 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance
White-Box Evaluation of Computer Vision Algorithms through Explicit Decision-Making
ICVS '09 Proceedings of the 7th International Conference on Computer Vision Systems: Computer Vision Systems
A method of automatic performance evaluation of table processing
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
Analysis and taxonomy of column header categories for web tables
DAS '10 Proceedings of the 9th IAPR International Workshop on Document Analysis Systems
An open approach towards the benchmarking of table structure recognition systems
DAS '10 Proceedings of the 9th IAPR International Workshop on Document Analysis Systems
Towards a common evaluation strategy for table structure recognition algorithms
Proceedings of the 10th ACM symposium on Document engineering
A platform for storing, visualizing, and interpreting collections of noisy documents
AND '10 Proceedings of the fourth workshop on Analytics for noisy unstructured text data
2D fast vessel visualization using a vessel wall mask guiding fine vessel detection
Journal of Biomedical Imaging - Special issue on mathematical methods for images and surfaces
Document analysis research in the year 2021
IEA/AIE'11 Proceedings of the 24th international conference on Industrial engineering and other applications of applied intelligent systems conference on Modern approaches in applied intelligence - Volume Part I
A methodology for evaluating algorithms for table understanding in PDF documents
Proceedings of the 2012 ACM symposium on Document engineering
A fast, efficient and automated method to extract vessels from fundus images
Journal of Visualization
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Abstract: The principle that for every document analysis task there exists a mechanism for creating well-defined ground-truth is widely held tenet. Past experience with standard datasets providing ground-truth for character recognition and page segmentation tasks supports this belief. In the process of attempting to evaluate several table recognition algorithms we have been developing, however, we have uncovered a number of serious hurdles connected with the ground-truthing of tables. This problem may, in fact, be much more difficult than it appears. We present a detailed analysis of why table ground-truthing is so hard, including the notions that there may exist more than one acceptable "truth" and/or incomplete or partial "truths."