25.2.2.3.12 Table Segmentation, Extract Tables or Forms, General

Watanabe, T., Luo, Q., Sugie, N.,
Layout Recognition of Multi-Kinds of Table-Form Documents,
PAMI(17), No. 4, April 1995, pp. 432-445.
IEEE DOI Extract the blocks in the table and then the contents. BibRef 9504

Watanabe, T., Luo, Q., Sugie, N.,
Structure recognition methods for various types of documents,
MVA(6), No. 2-3, 1993, pp. 163-176. BibRef 9300
Earlier:
A cooperative document understanding method among multiple recognition procedures,
ICPR92(II:689-692).
IEEE DOI 9208
BibRef

Watanabe, T., Luo, Q.,
A Multilayer Recognition Method for Understanding Table-Form Documents,
IJIST(7), No. 4, Winter 1996, pp. 279-288. 9612
BibRef

Chandran, S., Balasubramanian, S., Gandhi, T., Prasad, A., Kasturi, R., Chhabra, A.K.,
Structure Recognition and Information Extraction from Tabular Documents,
IJIST(7), No. 4, Winter 1996, pp. 289-303. 9612
BibRef

Yamashita, A.[Akio], Toyokawa, K.[Kazuharu],
Method and apparatus for a layout of a document image,
US_Patent5,555,362, September 10, 1996.
WWW Link. BibRef 9609

Yamashita, A., Amasno, T., Takahashi, H., Toyokawa, K.,
A Model Based Layout Understanding Method for the Document Recognition System,
ICDAR91(130-138). BibRef 9100

Lin, C.F., Hsiao, C.Y.,
Structural Recognition for Table-Form Documents using Relaxation Techniques,
PRAI(12), No. 7, November 1998, pp. 985. BibRef 9811

Hu, J., Kashi, R.S., Lopresti, D.P., Wilfong, G.T.,
Evaluating the performance of table processing algorithms,
IJDAR(4), No. 3, 2002, pp. 140-153.
Springer DOI 0205
Evaluation, Document Segmentation. BibRef

Hu, J.Y.[Jian-Ying], Kashi, R.S., Lopresti, D.P., Nagy, G., Wilfong, G.T.,
Why table ground-truthing is hard,
ICDAR01(129-133).
IEEE DOI 0109
BibRef

Lopresti, D.P., Wilfong, G.T.,
Evaluating document analysis results via graph probing,
ICDAR01(116-120).
IEEE DOI 0109
BibRef

Wang, Y.L.[Ya-Lin], Phillips, I.T.[Ihsin T.], Haralick, R.M.[Robert M.],
Table structure understanding and its performance evaluation,
PR(37), No. 7, July 2004, pp. 1479-1497.
Elsevier DOI 0405
Evaluation, Document Segmentation. BibRef
Earlier:
Table Detection via Probability Optimization,
DAS02(272 ff.).
Springer DOI 0303
BibRef
Earlier:
Automatic table ground truth generation and a background-analysis-based table structure extraction method,
ICDAR01(528-532).
IEEE DOI 0109

See also Document zone content classification and its performance evaluation. BibRef

Wang, Y.L.[Ya-Lin], Hu, J.Y.[Jian-Ying],
Detecting Tables in HTML Documents,
DAS02(249 ff.).
Springer DOI 0303
BibRef

Zanibbi, R.[Richard], Blostein, D.[Dorothea], Cordy, J.R.[James R.],
A survey of table recognition: Models, observations, transformations, and inferences,
IJDAR(7), No. 1, March 2004, pp. 1-16.
Springer DOI 0410
Survey, Document Segmentation. BibRef

Zanibbi, R.[Richard], Blostein, D.[Dorothea], Cordy, J.R.[James R.],
Historical recall and precision: summarizing generated hypotheses,
ICDAR05(I: 202-206).
IEEE DOI 0508
BibRef
And:
The Recognition Strategy Language,
ICDAR05(II: 565-569).
IEEE DOI 0508
Tables. BibRef

Li, Y.[Yi], Wang, Z.Y.[Zhi-Yan], Zeng, H.Z.[Hai-Zan],
Correlation Filter: An Accurate Approach to Detect and Locate Low Contrast Character Strings in Complex Table Environment,
PAMI(26), No. 12, December 2004, pp. 1639-1644.
IEEE Abstract. 0411
BibRef
Earlier:
String extraction from color airline coupon image using statistical approach,
ICDAR03(289-293).
IEEE DOI 0311
BibRef

Zlotnick, A.[Aviad],
Form recognition using reference areas,
US_Patent6,778,703, Aug 17, 2004
WWW Link. BibRef 0408

Zheng, Y.F.[Ye-Feng], Li, H.P.[Hui-Ping], Doermann, D.S.[David S.],
A Parallel-Line Detection Algorithm Based on HMM Decoding,
PAMI(27), No. 5, May 2005, pp. 777-792.
IEEE Abstract. 0501
BibRef
Earlier:
A model-based line detection algorithm in documents,
ICDAR03(44-48).
IEEE DOI 0311
Forms processing using groups of parallel lines. BibRef

Amano, A.[Akira], Asada, N.[Naoki], Mukunoki, M.[Masayuki], Aoyama, M.[Masahito],
Table form document analysis based on the document structure grammar,
IJDAR(8), No. 2-3, June 2006, pp. 201-213.
Springer DOI 0606
BibRef

Amano, A., Asada, N., Mukunoki, M.,
Modification table form generation system based on the form recognition,
ICPR04(II: 659-662).
IEEE DOI 0409
BibRef

Amano, A.[Akira], Asada, N.[Naoki],
Graph grammar based analysis system of complex table form document,
ICDAR03(916-920).
IEEE DOI 0311
BibRef
Earlier:
Complex Table Form Analysis Using Graph Grammar,
DAS02(283 ff.).
Springer DOI 0303
BibRef

Amano, A., Asada, N., Motoyama, T., Sumiyoshi, T., Suzuki, K.,
Table form document synthesis by grammar-based structure analysis,
ICDAR01(533-537).
IEEE DOI 0109
BibRef

Nielson, H.E., Barrett, W.A.,
Consensus-based table form recognition of low-quality historical documents,
IJDAR(8), No. 2-3, June 2006, pp. 183-200.
Springer DOI 0606
BibRef
Earlier:
Consensus-based table form recognition,
ICDAR03(906-910).
IEEE DOI 0311
BibRef

Coüasnon, B.[Bertrand],
DMOS, a generic document recognition method: application to table structure analysis in a general and in a specific way,
IJDAR(8), No. 2-3, June 2006, pp. 111-122.
Springer DOI 0606
BibRef
Earlier:
DMOS: a generic document recognition method, application to an automatic generator of musical scores, mathematical formulae and table structures recognition systems,
ICDAR01(215-220).
IEEE DOI 0109
BibRef

Couasnon, B.,
What can we learn from the processing of 165,000 forms from the 19th century?,
DIAL06(172-179).
IEEE DOI 0604
BibRef

Hurst, M.[Matthew],
Towards a theory of tables,
IJDAR(8), No. 2-3, June 2006, pp. 123-131.
Springer DOI 0606
BibRef
Earlier:
A constraint-based approach to table structure derivation,
ICDAR03(911-915).
IEEE DOI 0311
BibRef
Earlier:
Layout and language: exploring text block discovery in tables using linguistic resources,
ICDAR01(523-527).
IEEE DOI 0109
BibRef

Hurst, M., Douglas, S.,
Layout and Language: Preliminary Investigations in Recognizing the Structure of Tables,
ICDAR97(1043-1047).
IEEE DOI 9708
BibRef

de Silva, A.C.[Ana Costa], Jorge, A.M.[Alípio M.], Torgo, L.[Luís],
Design of an end-to-end method to extract information from tables,
IJDAR(8), No. 2-3, June 2006, pp. 144-171.
Springer DOI 0606
BibRef

Lin, Z.C.[Zhou-Chen], He, J.F.[Jun-Feng], Zhong, Z.C.[Zhi-Cheng], Wang, R.R.[Rong-Rong], Shum, H.Y.[Heung-Yeung],
Table Detection in Online Ink Notes,
PAMI(28), No. 8, August 2006, pp. 1341-1346.
IEEE DOI 0606

See also Rule-based cleanup of on-line English ink notes. BibRef

Zhang, X.W.[Xi-Wen], Lyu, M.R.[Michael R.], Dai, G.Z.[Guo-Zhong],
Extraction and segmentation of tables from Chinese ink documents based on a matrix model,
PR(40), No. 7, July 2007, pp. 1855-1867.
Elsevier DOI 0704
Chinese ink document; Digital ink; Handwriting; Table extraction; Table segmentation BibRef

Costa e Silva, A.[Ana],
Metrics for evaluating performance in document analysis: Application to tables,
IJDAR(14), No. 1, March 2011, pp. 101-109.
WWW Link. 1103
BibRef
Earlier:
Learning Rich Hidden Markov Models in Document Analysis: Table Location,
ICDAR09(843-847).
IEEE DOI 0907
BibRef

Chen, J.[Jin], Lopresti, D.P.[Daniel P.],
Model-based ruling line detection in noisy handwritten documents,
PRL(35), No. 1, 2014, pp. 34-45.
Elsevier DOI 1312
BibRef
Earlier:
A Model-Based Ruling Line Detection Algorithm for Noisy Handwritten Documents,
ICDAR11(404-408).
IEEE DOI 1111
Ruling line modeling BibRef

Chen, J.[Jin], Lopresti, D.P.[Daniel P.],
Model-Based Tabular Structure Detection and Recognition in Noisy Handwritten Documents,
FHR12(75-80).
IEEE DOI 1302
BibRef
And:
Table Detection in Noisy Off-line Handwritten Documents,
ICDAR11(399-403).
IEEE DOI 1111
BibRef

Lerouge, J.[Julien], Hammami, M.[Maroua], Héroux, P.[Pierre], Adam, S.[Sébastien],
Minimum cost subgraph matching using a binary linear program,
PRL(71), No. 1, 2016, pp. 45-51.
Elsevier DOI 1602
Subgraph matching BibRef

Hammami, M.[Maroua], Heroux, P.[Pierre], Adam, S.[Sebastien], d'Andecy, V.P.[Vincent Poulain],
One-shot field spotting on colored forms using subgraph isomorphism,
ICDAR15(586-590)
IEEE DOI 1511
BibRef

Tran, T.A.[Tuan Anh], Tran, H.T.[Hong Tai], Na, I.S.[In Seop], Lee, G.S.[Guee Sang], Yang, H.J.[Hyung Jeong], Kim, S.H.[Soo Hyung],
A mixture model using Random Rotation Bounding Box to detect table region in document image,
JVCIR(39), No. 1, 2016, pp. 196-208.
Elsevier DOI 1608
Table detection BibRef

Milosevic, N.[Nikola], Gregson, C.[Cassie], Hernandez, R.[Robert], Nenadic, G.[Goran],
A framework for information extraction from tables in biomedical literature,
IJDAR(22), No. 1, January 2019, pp. 55-78.
Springer DOI 1903
BibRef

Zhang, Z.R.[Zhen-Rong], Zhang, J.S.[Jian-Shu], Du, J.[Jun], Wang, F.R.[Feng-Ren],
Split, Embed and Merge: An accurate table structure recognizer,
PR(126), 2022, pp. 108565.
Elsevier DOI 2204
Table structure recognition, Self-regression, Attention mechanism, Encoder-decoder BibRef

Riba, P.[Pau], Goldmann, L.[Lutz], Terrades, O.R.[Oriol Ramos], Rusticus, D.[Diede], Fornés, A.[Alicia], Lladós, J.[Josep],
Table detection in business document images by message passing networks,
PR(127), 2022, pp. 108641.
Elsevier DOI 2205
Business document processing, Anonymized document processing, Table detection, Graph neural networks, Node and edge classification BibRef

Karthikeyan, S.[Srinidhi], de Herrera, A.G.S.[Alba G. Seco], Doctor, F.[Faiyaz], Mirza, A.[Asim],
An OCR Post-Correction Approach Using Deep Learning for Processing Medical Reports,
CirSysVideo(32), No. 5, May 2022, pp. 2574-2581.
IEEE DOI 2205
Optical character recognition software, Biomedical imaging, Medical services, Medical diagnostic imaging, Engines, medical documents BibRef

Li, X.H.[Xiao-Hui], Yin, F.[Fei], Dai, H.S.[He-Sen], Liu, C.L.[Cheng-Lin],
Table Structure Recognition and Form Parsing by End-to-End Object Detection and Relation Parsing,
PR(132), 2022, pp. 108946.
Elsevier DOI 2209
Table detection, Table structure recognition, Template-free form parsing, Graph neural network, End-to-end training BibRef

Ma, C.X.[Chi-Xiang], Lin, W.H.[Wei-Hong], Sun, L.[Lei], Huo, Q.[Qiang],
Robust Table Detection and Structure Recognition from Heterogeneous Document Images,
PR(133), 2023, pp. 109006.
Elsevier DOI 2210
Table detection, Table structure recognition, Corner detection, Spatial CNN, Grid CNN, Split-and-merge BibRef

Wang, J.W.[Jia-Wei], Lin, W.H.[Wei-Hong], Ma, C.[Chixiang], Li, M.Z.[Ming-Ze], Sun, Z.[Zheng], Sun, L.[Lei], Huo, Q.[Qiang],
Robust table structure recognition with dynamic queries enhanced detection transformer,
PR(144), 2023, pp. 109817.
Elsevier DOI 2310
Table structure recognition, Separation line regression, Two-stage DETR, Dynamic query BibRef

Su, S.[Shuai], Qu, J.[Jia], Cao, Y.[Yuan], Li, R.Q.[Ruo-Qing], Wang, G.[Guang],
Adversarial Training Lattice LSTM for Named Entity Recognition of Rail Fault Texts,
ITS(23), No. 11, November 2022, pp. 21201-21215.
IEEE DOI 2212
Rails, Task analysis, Training, Lattices, Hidden Markov models, Text recognition, Text analysis, Rail fault text, lattice LSTM BibRef

Wang, H.Y.[Hong-Yi], Xue, Y.[Yang], Zhang, J.X.[Jia-Xin], Jin, L.W.[Lian-Wen],
Scene table structure recognition with segmentation collaboration and alignment,
PRL(165), 2023, pp. 146-153.
Elsevier DOI 2301
Scene table structure recognition, Segmentation collaboration, Cell alignment BibRef

Granell, E.[Emilio], Romero, V.[Verónica], Prieto, J.R.[José Ramón], Andrés, J.[José], Quirós, L.[Lorenzo], Sánchez, J.A.[Joan Andreu], Vidal, E.[Enrique],
Processing a large collection of historical tabular images,
PRL(170), 2023, pp. 9-16.
Elsevier DOI 2306
Table recognition, Historical tabular images, Text recognition, Probabilistic indexing BibRef

Alexiou, M.S.[Michail S.], Bourbakis, N.G.[Nikolaos G.],
Behavioral analysis of bar charts in documents via stochastic petri-net modeling,
PRL(176), 2023, pp. 174-181.
Elsevier DOI 2312
Chart analysis, Document analysis and understanding, Stochastic petri-nets BibRef

Huang, J.[Jiani], Chen, H.H.[Hai-Hua], Yu, F.C.[Feng-Chang], Lu, W.[Wei],
From Detection to Application: Recent Advances in Understanding Scientific Tables and Figures,
Surveys(56), No. 10, June 2024, pp. xx-yy.
DOI Link 2407
Survey, Table Segmentation. Scientific documents, figure understanding, table understanding BibRef

Huang, Y.S.[Yong-Shuai], Lu, N.[Ning], Chen, D.P.[Da-Peng], Li, Y.[Yibo], Xie, Z.C.[Ze-Cheng], Zhu, S.G.[Sheng-Gao], Gao, L.[Liangcai], Peng, W.[Wei],
Improving Table Structure Recognition with Visual-Alignment Sequential Coordinate Modeling,
CVPR23(11134-11143)
IEEE DOI 2309
BibRef

del Bimbo, D.[Davide], Gemelli, A.[Andrea], Marinai, S.[Simone],
Data Augmentation on Graphs for Table Type Classification,
SSSPR22(242-252).
Springer DOI 2301
BibRef

Liu, Y.[Ying], Liang, X.Y.[Xiao-Yun], Chen, S.Q.[Shao-Qiong], Diao, L.[Liang], Tang, X.[Xin], Fang, R.[Rui], Chen, W.[Weifu],
Table information extraction and analysis: A robust geometric approach based on GatedGCN,
ICPR22(3131-3137)
IEEE DOI 2212
Image recognition, Optical character recognition, Semantics, Logic gates, Feature extraction, Information retrieval, Classification algorithms BibRef

Blomqvist, C.[Christopher], Enflo, K.[Kerstin], Jakobsson, A.[Andreas], Åström, K.[Kalle],
Joint Handwritten Text Recognition and Word Classification for Tabular Information Extraction,
ICPR22(1564-1570)
IEEE DOI 2212
Histograms, Image segmentation, Text recognition, Finance, Writing, Information retrieval, Decoding BibRef

Gemelli, A.[Andrea], Vivoli, E.[Emanuele], Marinai, S.[Simone],
Graph Neural Networks and Representation Embedding for Table Extraction in PDF Documents,
ICPR22(1719-1726)
IEEE DOI 2212
Text analysis, Image recognition, Text recognition, Pipelines, Optical character recognition, Merging, Layout BibRef

Levy, M.[Matan], Ben-Ari, R.[Rami], Lischinski, D.[Dani],
Classification-Regression for Chart Comprehension,
ECCV22(XXXVI:469-484).
Springer DOI 2211
BibRef

Smock, B.[Brandon], Pesala, R.[Rohith], Abraham, R.[Robin],
PubTables-1M: Towards comprehensive table extraction from unstructured documents,
CVPR22(4624-4632)
IEEE DOI 2210
Training, Object detection, Machine learning, Transformers, Functional analysis, Pattern recognition, Vision applications and systems BibRef

Nassar, A.[Ahmed], Livathinos, N.[Nikolaos], Lysak, M.[Maksym], Staar, P.[Peter],
TableFormer: Table Structure Understanding with Transformers,
CVPR22(4604-4613)
IEEE DOI 2210
Deep learning, Training, Shape, Optical character recognition, Object detection, Search engines, Transformers, retrieval, Recognition: detection BibRef

Liu, H.[Hao], Li, X.[Xin], Liu, B.[Bing], Jiang, D.Q.[De-Qiang], Liu, Y.[Yinsong], Ren, B.[Bo],
Neural Collaborative Graph Machines for Table Structure Recognition,
CVPR22(4523-4532)
IEEE DOI 2210
Visualization, Text analysis, Collaboration, Benchmark testing, Cognition, Pattern recognition, Visual reasoning BibRef

Wang, Y.F.[Yu-Fei], Du, C.[Chen], Xiao, B.H.[Bai-Hua],
FrameNet: Tabular Image Preprocessing Based on UNet and Adaptive Correction,
CIAP22(II:407-417).
Springer DOI 2205
BibRef

Ngo, P.[Phuc],
Digital Line Segment Detection for Table Reconstruction in Document Images,
CIAP22(II:211-224).
Springer DOI 2205
BibRef

Long, R.J.[Ru-Jiao], Wang, W.[Wen], Xue, N.[Nan], Gao, F.Y.[Fei-Yu], Yang, Z.B.[Zhi-Bo], Wang, Y.P.[Yong-Pan], Xia, G.S.[Gui-Song],
Parsing Table Structures in the Wild,
ICCV21(924-932)
IEEE DOI 2203
Training, Measurement, Layout, Web pages, Bending, Portable document format, Detection and localization in 2D and 3D BibRef

Xue, W.Y.[Wen-Yuan], Yu, B.[Baosheng], Wang, W.[Wen], Tao, D.C.[Da-Cheng], Li, Q.Y.[Qing-Yong],
TGRNet: A Table Graph Reconstruction Network for Table Structure Recognition,
ICCV21(1275-1284)
IEEE DOI 2203
Text analysis, Codes, Annotations, Layout, Predictive models, Benchmark testing, Scene text and document understanding, Vision + language BibRef

Raja, S.[Sachin], Mondal, A.[Ajoy], Jawahar, C.V.,
Visual Understanding of Complex Table Structures from Document Images,
WACV22(2543-2552)
IEEE DOI 2202
Visualization, Semantics, Layout, Linguistics, Benchmark testing, Information retrieval, Document Analysis BibRef

Zheng, X.Y.[Xin-Yi], Burdick, D.[Douglas], Popa, L.[Lucian], Zhong, X.[Xu], Wang, N.X.R.[Nancy Xin Ru],
Global Table Extractor (GTE): A Framework for Joint Table Identification and Cell Structure Recognition Using Visual Context,
WACV21(697-706)
IEEE DOI 2106
Training, Deep learning, Visualization, Systematics, Design methodology BibRef

Agarwal, M.[Madhav], Mondal, A.[Ajoy], Jawahar, C.V.,
CDeC-Net: Composite Deformable Cascade Network for Table Detection in Document Images,
ICPR21(9491-9498)
IEEE DOI 2105
Convolutional codes, Protocols, Convolution, Benchmark testing, Reproducibility of results, Mathematical model, Data mining, single model BibRef

Zhang, M.S.[Meng-Shi], Perelman, D.[Daniel], Le, V.[Vu], Gulwani, S.[Sumit],
An Integrated Approach of Deep Learning and Symbolic Analysis for Digital PDF Table Extraction,
ICPR21(4062-4069)
IEEE DOI 2105
Deep learning, Measurement, Location awareness, Machine learning algorithms, Semantics, Benchmark testing, Portable document format BibRef

Luo, J.Y.[Jun-Yu], Li, Z.K.[Ze-Kun], Wang, J.P.[Jin-Peng], Lin, C.Y.[Chin-Yew],
ChartOCR: Data Extraction from Charts Images via a Deep Hybrid Framework,
WACV21(1916-1924)
IEEE DOI 2106
Training, Deep learning, Computational modeling, Neural networks, Data visualization BibRef

Huang, D.Q.[Dan-Qing], Wang, J.P.[Jin-Peng], Wang, G.X.[Guo-Xin], Lin, C.Y.[Chin-Yew],
Visual Style Extraction from Chart Images for Chart Restyling,
ICPR21(7625-7632)
IEEE DOI 2105
Visualization, Art, Feature extraction, Encoding, Pattern recognition, Task analysis, Chart Restyling, Chart Style Extraction BibRef

Luo, J.Y.[Jun-Yu], Wang, J.[Jinpeng], Lin, C.Y.[Chin-Yew],
Hybrid Cascade Point Search Network for High Precision Bar Chart Component Detection,
ICPR21(6688-6695)
IEEE DOI 2105
Data visualization, Object detection, Pattern recognition, Task analysis, Bars BibRef

Wei, D.F.[Da-Feng], Lu, H.T.[Hong-Tao], Zhou, Y.[Yi], Chen, K.[Kai],
Image-based Table Cell Detection: a Novel Table Structure Decomposition Method with New Dataset,
ICPR21(1-7)
IEEE DOI 2105
Training, Deep learning, Adaptation models, Convolution, Annotations, Object detection, Pattern recognition BibRef

Li, Y.[Yiren], Huang, Z.[Zheng], Yan, J.C.[Jun-Chi], Zhou, Y.[Yi], Ye, F.[Fan], Liu, X.H.[Xian-Hui],
GFTE: Graph-based Financial Table Extraction,
DLPR20(644-658).
Springer DOI 2103
BibRef

Davila, K.[Kenny], Xu, F.[Fei], Ahmed, S.[Saleem], Mendoza, D.A.[David A.], Setlur, S.[Srirangaraj], Govindaraju, V.[Venu],
ICPR 2022: Challenge on Harvesting Raw Tables from Infographics (CHART-Infographics),
ICPR22(4995-5001)
IEEE DOI 2212
Training, Image recognition, Text recognition, Transformers, Data mining BibRef

Davila, K.[Kenny], Tensmeyer, C.[Chris], Shekhar, S.[Sumit], Singh, H.[Hrituraj], Setlur, S.[Srirangaraj], Govindaraju, V.[Venu],
ICPR 2020 - Competition on Harvesting Raw Tables from Infographics,
CHART20(361-380).
Springer DOI 2103
BibRef

Wang, C.[Chen], Cui, K.X.[Kai-Xu], Zhang, S.[Suya], Xu, C.L.[Chang-Liang],
Visual and Textual Information Fusion Method for Chart Recognition,
CHART20(381-389).
Springer DOI 2103
BibRef

Luo, Z.P.[Zhi-Peng], Zhang, Z.G.[Zhi-Guang], Li, G.[Ge], Che, L.X.[Li-Xuan], He, J.Y.[Jian-Ye], Xu, Z.Y.[Zhen-Yu],
A Benchmark for Analyzing Chart Images,
CHART20(390-400).
Springer DOI 2103
BibRef

Samari, A.[Arash], Piper, A.[Andrew], Hedley, A.[Alison], Cheriet, M.[Mohamed],
Weakly Supervised Bounding Box Extraction for Unlabeled Data in Table Detection,
PATRECH20(339-352).
Springer DOI 2103
BibRef

Zhong, X.[Xu], ShafieiBavani, E.[Elaheh], Yepes, A.J.[Antonio Jimeno],
Image-Based Table Recognition: Data, Model, and Evaluation,
ECCV20(XXI:564-580).
Springer DOI 2011
BibRef

Raja, S.[Sachin], Mondal, A.[Ajoy], Jawahar, C.V.,
Table Structure Recognition Using Top-down and Bottom-up Cues,
ECCV20(XXVIII:70-86).
Springer DOI 2011
BibRef

Prasad, D., Gadpal, A., Kapadni, K., Visave, M., Sultanpure, K.,
CascadeTabNet: An approach for end to end table detection and structure recognition from image-based documents,
WTDDL20(2439-2447)
IEEE DOI 2008
Task analysis, Image segmentation, Semantics, Head, Predictive models, Analytical models, Image recognition BibRef

Kavasidis, I., Pino, C., Palazzo, S., Rundo, F., Giordano, D., Messina, P., Spampinato, C.,
A Saliency-Based Convolutional Neural Network for Table and Chart Detection in Digitized Documents,
CIAP19(II:292-302).
Springer DOI 1909
BibRef

Alhéritière, H.[Héloïse], Amaïeur, W.[Walid], Cloppet, F.[Florence], Kurtz, C.[Camille], Ogier, J.M.[Jean-Marc], Vincent, N.[Nicole],
Straight Line Reconstruction for Fully Materialized Table Extraction in Degraded Document Images,
DGCI19(317-329).
Springer DOI 1905
BibRef

Che, X.Y.[Xiao-Yin], Yang, H.J.[Hao-Jin], Meinel, C.[Christoph],
Table Detection from Slide Images,
PSIVT15(762-774).
Springer DOI 1602
Presentation slides. BibRef

Liu, X.[Xiao], Tang, B.B.[Bin-Bin], Wang, Z.Y.[Zhen-Yang], Xu, X.H.[Xiang-Hua], Pu, S.L.[Shi-Liang], Tao, D.P.[Da-Peng], Song, M.L.[Ming-Li],
Chart classification by combining deep convolutional networks and deep belief networks,
ICDAR15(801-805)
IEEE DOI 1511
BibRef

Kasar, T., Bhowmik, T.K., Belaid, A.,
Table information extraction and structure recognition using query patterns,
ICDAR15(1086-1090)
IEEE DOI 1511
BibRef

Kasar, T., Barlas, P., Adam, S., Chatelain, C., Paquet, T.,
Learning to Detect Tables in Scanned Document Images Using Line Information,
ICDAR13(1185-1189)
IEEE DOI 1312
document image processing BibRef

Embley, D.W.[David W.], Seth, S.[Sharad], Nagy, G.[George],
Transforming Web Tables to a Relational Database,
ICPR14(2781-2786)
IEEE DOI 1412
Classification algorithms BibRef

Seth, S., Nagy, G.,
Segmenting Tables via Indexing of Value Cells by Table Headers,
ICDAR13(887-891)
IEEE DOI 1312
Internet BibRef

di Mauro, N., Esposito, F., Ferilli, S.,
Finding Critical Cells in Web Tables with SRL: Trying to Uncover the Devil's Tease,
ICDAR13(882-886)
IEEE DOI 1312
Internet BibRef

Shi, Z.X.[Zhi-Xin], Setlur, S., Govindaraju, V.,
A Model Based Framework for Table Processing in Degraded Document Images,
ICDAR13(963-967)
IEEE DOI 1312
document image processing BibRef

Gobel, M., Hassan, T., Oro, E., Orsi, G.,
ICDAR 2013 Table Competition,
ICDAR13(1449-1453)
IEEE DOI 1312
document image processing BibRef

Kim, S.C.[Seong-Chan], Liu, Y.[Ying],
Functional-Based Table Category Identification in Digital Library,
ICDAR11(1364-1368).
IEEE DOI 1111
BibRef

Nagy, G.[George], Seth, S.C.[Sharad C.], Jin, D.[Dongpu], Embley, D.W.[David W.], Machado, S.[Spencer], Krishnamoorthy, M.[Mukkai],
Data Extraction from Web Tables: The Devil is in the Details,
ICDAR11(242-246).
IEEE DOI 1111
BibRef

Liang, Y.H.[Yan-Hui], Wang, Y.Z.[Yi-Zhou], Saund, E.[Eric],
A Method of Evaluating Table Segmentation Results Based on a Table Image Ground Truther,
ICDAR11(247-251).
IEEE DOI 1111
BibRef

Deckert, F.[Florian], Seidler, B.[Benjamin], Ebbecke, M.[Markus], Gillmann, M.[Michael],
Table Content Understanding in SmartFIX,
ICDAR11(488-492).
IEEE DOI 1111
BibRef

Fang, J.[Jing], Gao, L.C.[Liang-Cai], Bai, K.[Kun], Qiu, R.H.[Rui-Heng], Tao, X.[Xin], Tang, Z.[Zhi],
A Table Detection Method for Multipage PDF Documents via Visual Seperators and Tabular Structures,
ICDAR11(779-783).
IEEE DOI 1111
BibRef

Mishchenko, A.[Ales], Vassilieva, N.[Natalia],
Model-Based Chart Image Classification,
ISVC11(II: 476-485).
Springer DOI 1109
e.g. financial documents BibRef

Xie, D.W.[Da-Wei], Zhou, Z.K.[Zhen-Kun], Wu, J.Q.[Jiang-Qin],
D-Note: Computer-Aided Digital Note Taking System on Physical Book,
ICIG11(963-968).
IEEE DOI 1109
Digitally make notes, not on the actual book. BibRef

Oro, E.[Ermelinda], Ruffolo, M.[Massimo],
PDF-TREX: An Approach for Recognizing and Extracting Tables from PDF Documents,
ICDAR09(906-910).
IEEE DOI 0907
BibRef

Long, V.[Vanessa],
An RDF-Based Blackboard Architecture for Improving Table Analysis,
ICDAR09(916-920).
IEEE DOI 0907
BibRef

Liu, Y.[Ying], Bai, K.[Kun], Mitra, P.[Prasenjit], Giles, C.L.[C. Lee],
Improving the Table Boundary Detection in PDFs by Fixing the Sequence Error of the Sparse Lines,
ICDAR09(1006-1010).
IEEE DOI 0907
BibRef

Hamza, H.[Hatem], Belaid, Y.[Yolande], Belaid, A.[Abdel], Chaudhuri, B.B.[Bidyut B.],
Incremental classification of invoice documents,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Jha, P.[Piyushee], Nagy, G.[George],
Wang Notation Tool: Layout independent representation of tables,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Minagawa, A., Fujii, Y., Takebe, H., Fujimoto, K.,
Logical Structure Analysis for Form Images with Arbitrary Layout by Belief Propagation,
ICDAR07(714-718).
IEEE DOI 0709
BibRef

Huang, W., Tan, C.L.,
Locating Charts from Scanned Document Pages,
ICDAR07(307-311).
IEEE DOI 0709
BibRef

Liu, Y., Bai, K., Mitra, P., Giles, C.L.,
Searching for Tables in Digital Documents,
ICDAR07(934-938).
IEEE DOI 0709
BibRef

Hassan, T., Baumgartner, R.,
Table Recognition and Understanding from PDF Files,
ICDAR07(1143-1147).
IEEE DOI 0709
BibRef

Huang, W.H.[Wei-Hua], Zong, S.Q.[Si-Qi], Tan, C.L.[Chew Lim],
Chart Image Classification Using Multiple-Instance Learning,
WACV07(27-27).
IEEE DOI 0702
BibRef

Hua, G.[Gang], Liu, Z.C.[Zi-Cheng], Zhang, Z.Y.[Zheng-You], Wu, Y.[Ying],
Automatic Business Card Scanning with a Camera,
ICIP06(373-376).
IEEE DOI 0610
BibRef

Alrashed, S.A.[Saleh A.],
Finding Hidden Semantics of Text Tables,
DAS06(449-461).
Springer DOI 0602
BibRef

Alrashed, S.A.[Saleh A.], Gray, W.A.,
Detection Approaches for Table Semantics in Text,
DAS02(287 ff.).
Springer DOI 0303
BibRef

Pereira Neves, L.A.[Luiz Antônio], de Carvalho, J.M.[João Marques], Facon, J.[Jacques], Bortolozzi, F.[Flávio], Ignácio, S.A.[Sérgio Aparecido],
Handwritten Artefact Identification Method for Table Interpretation with Little Use of Previous Knowledge,
DAS06(176-185).
Springer DOI 0602
BibRef

Embley, D.W.[David W.], Lopresti, D.P.[Daniel P.], Nagy, G.[George],
Notes on Contemporary Table Recognition,
DAS06(164-175).
Springer DOI 0602
BibRef

Kieninger, T., Dengel, A.R.,
An approach towards benchmarking of table structure recognition results,
ICDAR05(II: 1232-1236).
IEEE DOI 0508
BibRef
Earlier:
Applying the T-Recs table recognition system to the business letter domain,
ICDAR01(518-522).
IEEE DOI 0109
BibRef

Klein, B., Gokkus, S., Kieninger, T., Dengel, A.R.,
Three approaches to 'industrial' table spotting,
ICDAR01(513-517).
IEEE DOI 0109
BibRef

Ishitani, Y., Fume, K., Sumita, K.,
Table structure analysis based on cell classification and cell modification for XML document transformation,
ICDAR05(II: 1247-1252).
IEEE DOI 0508
BibRef

Long, V., Dale, R., Cassidy, S.,
A model for detecting and merging vertically spanned table cells in plain text documents,
ICDAR05(II: 1242-1246).
IEEE DOI 0508
BibRef

Kboubi, F., Chabi, A.H., Ahmed, M.B.,
Table recognition evaluation and combination methods,
ICDAR05(II: 1237-1241).
IEEE DOI 0508
BibRef

Kim, Y.S.[Yeon-Seok], Lee, K.H.[Kyong-Ho],
Extracting Table Information from the Web,
DAS04(438-441).
Springer DOI 0505
BibRef

Ohtera, R., Horiuchi, T.,
Faxed form identification using histogram of the hough-space,
ICPR04(II: 566-569).
IEEE DOI 0409
BibRef

Ramel, J.Y., Crucianu, M., Vincent, N., Faure, C.,
Detection, extraction and representation of tables,
ICDAR03(374-378).
IEEE DOI 0311
BibRef

Wasserman, H.[Howard], Yukawa, K.[Keitaro], Sy, B.[Bon], Kwok, K.L.[Kui-Lam], Phillips, I.T.[Ihsin T.],
A Theoretical Foundation and a Method for Document Table Structure Extraction and Decomposition,
DAS02(291 ff.).
Springer DOI 0303
BibRef

Cesarini, F., Marinai, S., Sarti, L., Soda, G.,
Trainable table location in document images,
ICPR02(III: 236-240).
IEEE DOI 0211
BibRef

Tsuruoka, S., Takao, K., Tanaka, T., Yoshikawa, T., Shinogi, T.,
Region segmentation for table image with unknown complex structure,
ICDAR01(709-713).
IEEE DOI 0109
BibRef

Zuyev, K.,
Table Image Segmentation,
ICDAR97(705-708).
IEEE DOI 9708
BibRef

Chen, J.S.[Jain-Shiue], Tseng, D.C.[Din-Chang],
Overlapped-Character Separation and Reconstruction for Table-Form Documents,
ICIP96(II: 233-236).
IEEE DOI 9610
BibRef

Arias, J.F.[Juan F.], Chhabra, A.[Atul], and Misra, V.[Vishal],
Interpreting and Representing Tabular Documents,
CVPR96(600-605).
IEEE DOI BibRef 9600
Earlier:
Efficient Interpretation of Tabular Documents,
ICPR96(III: 681-685).
IEEE DOI 9608
(NYNEX Science and Technology, USA) BibRef

Watanabe, T., Huang, X.,
Automatic Acquisition of Layout Knowledge for Understanding Business Cards,
ICDAR97(216-220).
IEEE DOI 9708
BibRef

Saiga, H., Kitamura, Y., Ida, S.,
High-speed recognition of tabulated data,
ICPR94(B:577-579).
IEEE DOI 9410
BibRef

Laurentini, A., Viada, P.,
Identifying and understanding tabular material in compound documents,
ICPR92(II:405-409).
IEEE DOI 9208
BibRef

Kreich, J., Luhn, A., Maderlechner, G.,
An Experimental Environment for Model Based Document Analysis,
ICDAR91(50-58). BibRef 9100

Chapter on OCR, Document Analysis and Character Recognition Systems continues in
Document Layout, Structure Analysis, Web Documents, Online Documents .