- -

Discriminative estimation of probabilistic context-free grammars for mathematical expression recognition and retrieval

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Compartir/Enviar a

Citas

Estadísticas

  • Estadisticas de Uso

Discriminative estimation of probabilistic context-free grammars for mathematical expression recognition and retrieval

Mostrar el registro completo del ítem

Noya García, E.; Benedí Ruiz, JM.; Sánchez Peiró, JA.; Anitei, D. (2023). Discriminative estimation of probabilistic context-free grammars for mathematical expression recognition and retrieval. Pattern Analysis and Applications. 26:1571-1584. https://doi.org/10.1007/s10044-023-01158-8

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/200855

Ficheros en el ítem

Thumbnail
Nombre: NoyaBenediSanchez ...
Tamaño: 1.599Mb
Formato: PDF
Descripción: Versión editorial
Abrir/Preview

Metadatos del ítem

Título: Discriminative estimation of probabilistic context-free grammars for mathematical expression recognition and retrieval
Autor: Noya García, Ernesto Benedí Ruiz, José Miguel Sánchez Peiró, Joan Andreu Anitei, Dan
Entidad UPV: Universitat Politècnica de València. Escola Tècnica Superior d'Enginyeria Informàtica
Fecha difusión:
Resumen:
[EN] We present a discriminative learning algorithm for the probabilistic estimation of two-dimensional probabilistic context-free grammars (2D-PCFG) for mathematical expressions recognition and retrieval. This algorithm ...[+]
Palabras clave: Discriminative learning , Two-dimensional probabilistic context-free grammars , Mathematical expression retrieval , Probabilistic indexing
Derechos de uso: Reconocimiento (by)
Fuente:
Pattern Analysis and Applications. (issn: 1433-7541 )
DOI: 10.1007/s10044-023-01158-8
Editorial:
Springer-Verlag
Versión del editor: https://doi.org/10.1007/s10044-023-01158-8
Código del Proyecto:
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-116813RB-I00/ES/SEARCHING IN THE SIMANCA ARCHIVE/
info:eu-repo/grantAgreement/GENERALITAT VALENCIANA//CIACIF%2F2021%2F313//Indexación y búsqueda de expresiones matemáticas basada en redes neuronales profundas para colecciones masivas de imágenes de documentos científicos/
info:eu-repo/grantAgreement/UPV//SP20210263/
Agradecimientos:
This research has been developed with the support of Grant PID2020-116813RBI00a funded by MCIN/AEI/ 10.13039/501100011033 and FPI grant CIACIF/2021/313 funded by Generalitat Valenciana. Universitat Politecnica de Valencia ...[+]
Tipo: Artículo

References

Bahl LR, Jelinek F, Mercer RL (1983) A maximum likelihood approach to continuous speech recognition. IEEE Trans Pattern Anal Machine Intell 5(2):179–190

Koehn P (2009) Statistical Machine Translation. Cambridge University Press, ???. https://doi.org/10.1017/CBO9780511815829

Graves A, Fernández S, Gomez F, Schmidhuber J (2006) Connectionist temporal classification: Labelling unsegmented sequence data with recurrent neural networks. In: ICML, vol 2006, pp 369–376. https://doi.org/10.1145/1143844.1143891 [+]
Bahl LR, Jelinek F, Mercer RL (1983) A maximum likelihood approach to continuous speech recognition. IEEE Trans Pattern Anal Machine Intell 5(2):179–190

Koehn P (2009) Statistical Machine Translation. Cambridge University Press, ???. https://doi.org/10.1017/CBO9780511815829

Graves A, Fernández S, Gomez F, Schmidhuber J (2006) Connectionist temporal classification: Labelling unsegmented sequence data with recurrent neural networks. In: ICML, vol 2006, pp 369–376. https://doi.org/10.1145/1143844.1143891

Marzal A (1993) Cálculo de las k mejores soluciones a problemas de programación dinámica. PhD thesis, Universidad Politécnica de Valencia

Jiménez VM, Marzal A (2000) Computation of the N Best Parse Trees for Weighted and Stochastic Context-Free Grammars. In: Advances in Pattern Recognition. Lecture Notes in Computer Science, 1876, pp 183–192 https://doi.org/10.1007/3-540-44522-6_19

Ortmanns S, Ney H, Aubert X (1997) A word graph algorithm for large vocabulary continuous speech recognition. Comput Speech Lang 11(1):43–72. https://doi.org/10.1006/csla.1996.0022

Noya E, Sánchez JA, Benedí JM (2021) Generation of Hypergraphs from the N-Best Parsing of 2D-Probabilistic Context-Free Grammars for Mathematical Expression Recognition. In: ICPR, pp 5696–5703. https://doi.org/10.1109/ICPR48806.2021.9412273

Ueffing N, Och FJ, Ney H (2002) Generation of word graphs in statistical machine translation. In: Proceedings of the 2002 conference on empirical methods in natural language processing (EMNLP 2002), pp 156–163. Association for Computational Linguistics, ???. https://doi.org/10.3115/1118693.1118714. https://aclanthology.org/W02-1021

Toselli AH, Vidal E, Puigcerver J, Noya-García E (2019) Probabilistic multi-word spotting in handwritten text images. Pattern Anal Appl 22:23–32. https://doi.org/10.1007/s10044-018-0742-z

Sánchez-Sáez R, Sánchez JA, Benedí JM (2010) Confidence measures for error discrimination in an interactive predictive parsing framework. In: Coling, pp 1220–1228

Benedí JM, Sánchez JA (2005) Estimation of stochastic context-free grammars and their use as language models. Comput Speech Lang 19(3):249–274. https://doi.org/10.1016/j.csl.2004.09.001

Awal AM, Mouchère H, Viard-Gaudin C (2012) A global learning approach for an online handwritten mathematical expression recognition system. Pattern Recogn Lett 35:68–77. https://doi.org/10.1016/j.patrec.2012.10.024

Álvaro F, Sánchez JA, Benedí JM (2016) An Integrated Grammar-based Approach for Mathematical Expression Recognition. Pattern Recogn 51:135–147. https://doi.org/10.1016/j.patcog.2015.09.013

Deng Y, Kanervisto A, Ling J, Rush AM (2017) Image-to-markup generation with coarse-to-fine attention. In: Proceedings of the ICML-17, pp 980–989

Anitei D, Sánchez JA, Fuentes JM, Paredes R, Benedí JM (2021) ICDAR2021 Competition on mathematical formula detection. In: ICDAR, pp 783–795. https://doi.org/10.1007/978-3-030-86337-1_52

Gopalakrishnan PS, Kanevsky D, Nadas A, Nahamoo D (1991) An inequality for rational functions with applications to some statistical estimation problems. IEEE Trans Inf Theory 37(1):107–113. https://doi.org/10.1109/18.61108

Maca M, Benedí JM, Sánchez JA (2021) Discriminative Learning for Probabilistic Context-Free Grammars based on Generalized H-Criterion. Preprint arXiv:2103.08656arXiv:2103.08656 [cs.CL]

Woodland PC, Povey D (2002) Large scale discriminative training of hidden Markov models for speech recognition. Comput Speech Lang 16(1):25–47. https://doi.org/10.1006/csla.2001.0182

Noya E, Benedí JM, Sánchez JA, Anitei D (2022) Discriminative learning of two-dimensional probabilistic context-free grammars for mathematical expression recognition and retrieval. In: IbPRIA, pp 333–347. https://doi.org/10.1007/978-3-031-04881-4_27

Zanibbi R, Blostein D (2011) Recognition and Retrieval of Mathematical Expressions. IJDAR 15:331–357. https://doi.org/10.1007/s10032-011-0174-4

Huang J, Tan J, Bi N (2020) Overview of mathematical expression recognition. In: Pattern recognition and artificial intelligence, pp 41–54. https://doi.org/10.1007/978-3-030-59830-3_4

Mahdavi M, Zanibbi R, Mouchere H, Viard-Gaudin C, Garain U (2019) ICDAR 2019 CROHME + TFD: Competition on recognition of handwritten mathematical expressions and typeset formula detection. In: ICDAR, pp 1533–1538. https://doi.org/10.1109/ICDAR.2019.00247

Wang DH, Yin F, Wu JW, Yan YP, Huang ZC, Chen GY, Wang Y, Liu CL (2020) ICFHR 2020 Competition on offline recognition and spotting of handwritten mathematical expressions - OffRaSHME. In: ICFHR, pp. 211–215. https://doi.org/10.1109/ICFHR2020.2020.00047

Wan Z, Fan K, Wang Q, Zhang S (2019) Recognition of printed mathematical formula symbols based on convolutional neural network. DEStech Transactions on Computer Science and Engineering. https://doi.org/10.12783/dtcse/ica2019/30711

Wu J-W, Yin F, Zhang Y-M, Zhang X-Y, Liu C-L (2020) Handwritten mathematical expression recognition via paired adversarial learning. Int J Comput Vis 128:2386–401. https://doi.org/10.1007/s11263-020-01291-5

Peng S, Gao L, Yuan K, Tang Z (2021) Image to LaTeX with Graph Neural Network for Mathematical Formula Recognition. In: ICDAR, pp 648–663. https://doi.org/10.1007/978-3-030-86331-9_42

Zhao W, Gao L, Yan Z, Peng S, Du L, Zhang Z (2021) Handwritten mathematical expression recognition with bidirectionally trained transformer. In: Document analysis and recognition – ICDAR 2021, pp 570–584. https://doi.org/10.1007/978-3-030-86331-9_37

Davila K, Joshi R, Setlur S, Govindaraju V, Zanibbi R (2019) Tangent-V: Math formula image search using line-of-sight graphs, pp 681–695. https://doi.org/10.1007/978-3-030-15712-8_44

Zhong W, Zanibbi R (2019) Structural similarity search for formulas using leaf-root paths in operator subtrees, pp 116–129. https://doi.org/10.1007/978-3-030-15712-8_8

Mansouri B, Zanibbi R, Oard D (2019) Characterizing searches for mathematical concepts, pp 57–66. https://doi.org/10.1109/JCDL.2019.00019

Chou PA (1989) Recognition of equations using a two-dimensional stochastic context-free grammar. In: Visual communications and image processing IV, vol 1199, pp 852–863. https://doi.org/10.1117/12.970095

Pr$$\mathring{u}$$ša D, Hlaváč V (2007) Mathematical Formulae Recognition Using 2D Grammars. ICDAR 2, 849–853. https://doi.org/10.1109/ICDAR.2007.4377035

Lari K, Young SJ (1991) Applications of stochastic context-free grammars using the inside-outside algorithm. Comput Speech Lang 5(3):237–257. https://doi.org/10.1016/0885-2308(91)90009-F

Ney H (1992) Stochastic grammars and pattern recognition. In: Laface, P., De Mori, R. (eds.) Speech recognition and understanding, pp 319–344. https://doi.org/10.1007/978-3-642-76626-8_34

Baum LE, Sell GR (1968) Growth transformation for functions on manifolds. Pac J Math 27(2):211–227

Casacuberta F (1996) Growth transformations for probabilistic functions of stochastic grammars. IJPRAI 10(3):183–201. https://doi.org/10.1142/S0218001496000153

Gopalakrishnan P, Kanevsky D, Nadas A, Nahamoo D, Picheny M (1988) Decoder selection based on cross-entropies. In: ICASSP-88, vol 1, pp 20–23. https://doi.org/10.1109/ICASSP.1988.196499

Papineni K, Roukos S, Ward T, Zhu WJ (2002) BLEU: a method for automatic evaluation of machine translation. In: ACL, pp 311–318. https://doi.org/10.3115/1073083.1073135

Suzuki M, Tamari F, Fukuda R, Uchida S, Kanahori T (2003) Infty: an integrated ocr system for mathematical documents, pp 95–104. https://doi.org/10.1145/958220.958239

Shi B, Bai X, Yao C (2017) An end-to-end trainable neural network for image-based sequence recognition and its application to scene text recognition. TPAMI 39–11:2298–2304. https://doi.org/10.1109/TPAMI.2016.2646371

Singh S (2018) Teaching machines to code: neural markup generation with visual attention. Preprint arXiv:1802.05415arXiv:1802.05415 [cs.CL]

[-]

recommendations

 

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro completo del ítem