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2020 – today
- 2020
[j10]Brian Kenji Iwana, Volkmar Frinken, Seiichi Uchida:
DTW-NN: A novel neural network for time series recognition using dynamic alignment between inputs and weights. Knowl. Based Syst. 188 (2020)
2010 – 2019
- 2018
- [c40]Volkmar Frinken, Satish Ravindran, Shriphani Palakodety, Guha Jayachandran, Nilesh Powar:
Video and Audio Data Extraction for Retrieval, Ranking and Recapitulation (VADER ^3 ). ANNPR 2018: 359-370 - 2017
- [j9]Brian Kenji Iwana, Volkmar Frinken, Kaspar Riesen
, Seiichi Uchida:
Efficient temporal pattern recognition by means of dissimilarity space embedding with discriminative prototypes. Pattern Recognit. 64: 268-276 (2017) - 2016
- [j8]Alejandro Héctor Toselli Rossi, Enrique Vidal, Verónica Romero, Volkmar Frinken:
HMM word graph based keyword spotting in handwritten document images. Inf. Sci. 370-371: 497-518 (2016) - [c39]Brian Kenji Iwana, Volkmar Frinken, Seiichi Uchida:
A Robust Dissimilarity-Based Neural Network for Temporal Pattern Recognition. ICFHR 2016: 265-270 - [p2]Marcus Liwicki, Volkmar Frinken, Muhammad Zeshan Afzal:
Latest Developments of LSTM Neural Networks with Applications of Document Image Analysis. Handbook of Pattern Recognition and Computer Vision 2016: 293-311 - 2015
- [j7]Andreas Fischer, Ching Y. Suen, Volkmar Frinken, Kaspar Riesen, Horst Bunke:
Approximation of graph edit distance based on Hausdorff matching. Pattern Recognit. 48(2): 331-343 (2015) - [c38]Nilanjana Bhattacharya, Volkmar Frinken, Umapada Pal, Partha Pratim Roy:
Overwriting repetition and crossing-out detection in online handwritten text. ACPR 2015: 680-684 - [c37]Andreas Fischer, Seiichi Uchida, Volkmar Frinken, Kaspar Riesen, Horst Bunke:
Improving Hausdorff Edit Distance Using Structural Node Context. GbRPR 2015: 148-157 - [c36]Donato Barbuzzi, Giuseppe Pirlo, Seiichi Uchida, Volkmar Frinken, Donato Impedovo:
Similarity-based regularization for semi-supervised learning for handwritten digit recognition. ICDAR 2015: 101-105 - [c35]Ryosuke Kakisako, Seiichi Uchida, Volkmar Frinken:
Learning non-Markovian constraints for handwriting recognition. ICDAR 2015: 446-450 - [c34]Brian Kenji Iwana, Seiichi Uchida, Kaspar Riesen, Volkmar Frinken:
Tackling temporal pattern recognition by vector space embedding. ICDAR 2015: 816-820 - [c33]Volkmar Frinken, Seiichi Uchida:
Deep BLSTM neural networks for unconstrained continuous handwritten text recognition. ICDAR 2015: 911-915 - 2014
- [j6]Marçal Rusiñol, Volkmar Frinken, Dimosthenis Karatzas, Andrew D. Bagdanov, Josep Lladós:
Multimodal page classification in administrative document image streams. Int. J. Document Anal. Recognit. 17(4): 331-341 (2014) - [j5]Volkmar Frinken, Andreas Fischer, Markus Baumgartner, Horst Bunke:
Keyword spotting for self-training of BLSTM NN based handwriting recognition systems. Pattern Recognit. 47(3): 1073-1082 (2014) - [j4]Francisco Zamora-Martínez, Volkmar Frinken, Salvador España Boquera, María José Castro Bleda, Andreas Fischer, Horst Bunke:
Neural network language models for off-line handwriting recognition. Pattern Recognit. 47(4): 1642-1652 (2014) - [c32]Volkmar Frinken, Dimosthenis Karatzas, Andreas Fischer:
A Cache Language Model for Whole Document Handwriting Recognition. Document Analysis Systems 2014: 166-170 - [c31]Volkmar Frinken, Nilanjana Bhattacharya, Umapada Pal:
Design of Unsupervised Feature Extraction System for On-line Bangla Handwriting Recognition. Document Analysis Systems 2014: 355-359 - [c30]Volkmar Frinken, Ryosuke Kakisako, Seiichi Uchida:
A Novel HMM Decoding Algorithm Permitting Long-Term Dependencies and Its Application to Handwritten Word Recognition. ICFHR 2014: 128-133 - [c29]Ryota Ogata, Minoru Mori, Volkmar Frinken, Seiichi Uchida:
Constrained AdaBoost for Totally-Ordered Global Features. ICFHR 2014: 393-398 - [c28]Muhammad Imran Malik, Marcus Liwicki, Andreas Dengel, Seiichi Uchida, Volkmar Frinken:
Automatic Signature Stability Analysis and Verification Using Local Features. ICFHR 2014: 621-626 - [c27]Kohei Inai, Marten Palsson, Volkmar Frinken, Yaokai Feng, Seiichi Uchida:
Selective Concealment of Characters for Privacy Protection. ICPR 2014: 333-338 - [c26]Volkmar Frinken, Yutaro Iwakiri, Ryosuke Ishida, Kensho Fujisaki, Seiichi Uchida:
Improving Point of View Scene Recognition by Considering Textual Data. ICPR 2014: 2966-2971 - [c25]Volkmar Frinken, Nilanjana Bhattacharya, Seiichi Uchida, Umapada Pal:
Improved BLSTM Neural Networks for Recognition of On-Line Bangla Complex Words. S+SSPR 2014: 404-413 - [p1]Volkmar Frinken, Horst Bunke:
Continuous Handwritten Script Recognition. Handbook of Document Image Processing and Recognition 2014: 391-425 - 2013
- [j3]Verónica Romero, Alicia Fornés, Nicolás Serrano, Joan-Andreu Sánchez, Alejandro H. Toselli, Volkmar Frinken, Enrique Vidal, Josep Lladós:
The ESPOSALLES database: An ancient marriage license corpus for off-line handwriting recognition. Pattern Recognit. 46(6): 1658-1669 (2013) - [c24]Andreas Fischer, Ching Y. Suen, Volkmar Frinken, Kaspar Riesen, Horst Bunke:
A Fast Matching Algorithm for Graph-Based Handwriting Recognition. GbRPR 2013: 194-203 - [c23]Núria Cirera, Alicia Fornés, Volkmar Frinken, Josep Lladós:
Hybrid Grammar Language Model for Handwritten Historical Documents Recognition. IbPRIA 2013: 117-124 - [c22]Volkmar Frinken, Andreas Fischer, Carlos D. Martínez-Hinarejos:
Handwriting recognition in historical documents using very large vocabularies. HIP@ICDAR 2013: 67-72 - [c21]Andreas Fischer, Volkmar Frinken, Horst Bunke, Ching Y. Suen:
Improving HMM-Based Keyword Spotting with Character Language Models. ICDAR 2013: 506-510 - [e1]Volkmar Frinken, Bill Barrett, R. Manmatha, Volker Märgner:
Proceedings of the 2nd International Workshop on Historical Document Imaging and Processing, HIP@ICDAR 2013, Washington, DC, USA, August 24, 2013. ACM 2013, ISBN 978-1-4503-2115-0 [contents] - 2012
- [j2]Volkmar Frinken, Andreas Fischer, R. Manmatha, Horst Bunke:
A Novel Word Spotting Method Based on Recurrent Neural Networks. IEEE Trans. Pattern Anal. Mach. Intell. 34(2): 211-224 (2012) - [j1]Andreas Fischer, Andreas Keller, Volkmar Frinken, Horst Bunke:
Lexicon-free handwritten word spotting using character HMMs. Pattern Recognit. Lett. 33(7): 934-942 (2012) - [c20]Volkmar Frinken, Markus Baumgartner, Andreas Fischer, Horst Bunke:
Semi-supervised Learning for Cursive Handwriting Recognition Using Keyword Spotting. ICFHR 2012: 49-54 - [c19]Emanuel Indermühle, Volkmar Frinken, Horst Bunke:
Mode Detection in Online Handwritten Documents Using BLSTM Neural Networks. ICFHR 2012: 302-307 - [c18]Volkmar Frinken, Francisco Zamora-Martínez, Salvador España Boquera, María José Castro Bleda, Andreas Fischer, Horst Bunke:
Long-short term memory neural networks language modeling for handwriting recognition. ICPR 2012: 701-704 - [c17]Volkmar Frinken, Alicia Fornés, Josep Lladós, Jean-Marc Ogier:
Bidirectional Language Model for Handwriting Recognition. SSPR/SPR 2012: 611-619 - 2011
- [c16]Andreas Fischer, Volkmar Frinken, Alicia Fornés, Horst Bunke:
Transcription alignment of Latin manuscripts using hidden Markov models. HIP@ICDAR 2011: 29-36 - [c15]Andreas Fischer, Emanuel Indermühle, Volkmar Frinken, Horst Bunke:
HMM-Based Alignment of Inaccurate Transcriptions for Historical Documents. ICDAR 2011: 53-57 - [c14]Emanuel Indermühle, Volkmar Frinken, Andreas Fischer, Horst Bunke:
Keyword Spotting in Online Handwritten Documents Containing Text and Non-text Using BLSTM Neural Networks. ICDAR 2011: 73-77 - [c13]Alicia Fornés, Volkmar Frinken, Andreas Fischer, Jon Almazán, Gabriel Jackson, Horst Bunke:
A keyword spotting approach using blurred shape model-based descriptors. HIP@ICDAR 2011: 83-90 - [c12]Raman Jain, Volkmar Frinken, C. V. Jawahar, Raghavan Manmatha:
BLSTM Neural Network Based Word Retrieval for Hindi Documents. ICDAR 2011: 83-87 - [c11]Volkmar Frinken, Andreas Fischer, Horst Bunke, Alicia Fornés:
Co-training for Handwritten Word Recognition. ICDAR 2011: 314-318 - [c10]Volkmar Frinken, Andreas Fischer, Horst Bunke:
Improving handwritten keyword spotting with self-training. SAC 2011: 840-845 - 2010
- [c9]Volkmar Frinken, Andreas Fischer, Horst Bunke:
A Novel Word Spotting Algorithm Using Bidirectional Long Short-Term Memory Neural Networks. ANNPR 2010: 185-196 - [c8]Volkmar Frinken, Horst Bunke:
Self-training for Handwritten Text Line Recognition. CIARP 2010: 104-112 - [c7]Volkmar Frinken, Andreas Fischer, Horst Bunke, R. Manmatha:
Adapting BLSTM Neural Network Based Keyword Spotting Trained on Modern Data to Historical Documents. ICFHR 2010: 352-357 - [c6]Andreas Fischer, Andreas Keller, Volkmar Frinken, Horst Bunke:
HMM-based Word Spotting in Handwritten Documents Using Subword Models. ICPR 2010: 3416-3419 - [c5]Volkmar Frinken, Andreas Fischer, Horst Bunke:
Combining Neural Networks to Improve Performance of Handwritten Keyword Spotting. MCS 2010: 215-224
2000 – 2009
- 2009
- [c4]Volkmar Frinken, Tim Peter, Andreas Fischer, Horst Bunke, Trinh Minh Tri Do, Thierry Artières:
Improved Handwriting Recognition by Combining Two Forms of Hidden Markov Models and a Recurrent Neural Network. CAIP 2009: 189-196 - [c3]Kaspar Riesen, Volkmar Frinken, Horst Bunke:
Improving Graph Classification by Isomap. GbRPR 2009: 205-214 - [c2]Volkmar Frinken, Horst Bunke:
Evaluating Retraining Rules for Semi-Supervised Learning in Neural Network Based Cursive Word Recognition. ICDAR 2009: 31-35 - [c1]Volkmar Frinken, Horst Bunke:
Self-training Strategies for Handwriting Word Recognition. ICDM 2009: 291-300
Coauthor Index
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