{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,2]],"date-time":"2026-08-02T19:26:29Z","timestamp":1785698789897,"version":"3.56.0"},"publisher-location":"Cham","reference-count":46,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031784941","type":"print"},{"value":"9783031784958","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,12,4]],"date-time":"2024-12-04T00:00:00Z","timestamp":1733270400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,12,4]],"date-time":"2024-12-04T00:00:00Z","timestamp":1733270400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-3-031-78495-8_19","type":"book-chapter","created":{"date-parts":[[2024,12,3]],"date-time":"2024-12-03T09:46:26Z","timestamp":1733219186000},"page":"297-315","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["CHART-Info 2024: A Dataset for\u00a0Chart Analysis and\u00a0Recognition"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6308-7113","authenticated-orcid":false,"given":"Kenny","family":"Davila","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-9482-3230","authenticated-orcid":false,"given":"Rupak","family":"Lazarus","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9353-9528","authenticated-orcid":false,"given":"Fei","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4405-7063","authenticated-orcid":false,"given":"Nicole","family":"Rodr\u00edguez Alc\u00e1ntara","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7118-9280","authenticated-orcid":false,"given":"Srirangaraj","family":"Setlur","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5318-7409","authenticated-orcid":false,"given":"Venu","family":"Govindaraju","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4808-8860","authenticated-orcid":false,"given":"Ajoy","family":"Mondal","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6767-7057","authenticated-orcid":false,"given":"C. V.","family":"Jawahar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,12,4]]},"reference":[{"key":"19_CR1","unstructured":"Tesseract OCR \u2013 opensource.google.com. https:\/\/opensource.google.com\/projects\/tesseract"},{"issue":"3","key":"19_CR2","doi-asserted-by":"publisher","first-page":"721","DOI":"10.3390\/ani11030721","volume":"11","author":"K Adamczyk","year":"2021","unstructured":"Adamczyk, K., Grzesiak, W., Zaborski, D.: The use of artificial neural networks and a general discriminant analysis for predicting culling reasons in Holstein-Friesian cows based on first-lactation performance records. Animals 11(3), 721 (2021)","journal-title":"Animals"},{"issue":"5","key":"19_CR3","doi-asserted-by":"publisher","first-page":"136","DOI":"10.3390\/jimaging8050136","volume":"8","author":"F Baji\u0107","year":"2022","unstructured":"Baji\u0107, F., Job, J.: Data extraction of circular-shaped and grid-like chart images. J. Imaging 8(5), 136 (2022)","journal-title":"J. Imaging"},{"key":"19_CR4","doi-asserted-by":"publisher","first-page":"896","DOI":"10.1016\/j.dib.2018.05.099","volume":"19","author":"R Bryce","year":"2018","unstructured":"Bryce, R., Carre\u00f1o, I.L., Kumler, A., Hodge, B.M., Roberts, B., Martinez-Anido, C.B.: Annually and monthly resolved solar irradiance and atmospheric temperature data across the Hawaiian archipelago from 1998 to 2015 with interannual summary statistics. Data Brief 19, 896\u2013920 (2018)","journal-title":"Data Brief"},{"key":"19_CR5","doi-asserted-by":"crossref","unstructured":"Chagas, P., et al.: Architecture proposal for data extraction of chart images using convolutional neural network. In: 21st IV, pp. 318\u2013323. IEEE (2017)","DOI":"10.1109\/iV.2017.37"},{"issue":"4","key":"19_CR6","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0060243","volume":"8","author":"J Chen","year":"2013","unstructured":"Chen, J., Cai, Y., Clark, M., Yu, Y.: Equilibrium and kinetic studies of phosphate removal from solution onto a hydrothermally modified oyster shell material. PLoS ONE 8(4), e60243 (2013)","journal-title":"PLoS ONE"},{"key":"19_CR7","doi-asserted-by":"crossref","unstructured":"Chollet, F.: Xception: deep learning with depthwise separable convolutions. In: Proceedings of CVPR, pp. 1251\u20131258 (2017)","DOI":"10.1109\/CVPR.2017.195"},{"issue":"11","key":"19_CR8","doi-asserted-by":"publisher","first-page":"3799","DOI":"10.1109\/TPAMI.2020.2992028","volume":"43","author":"K Davila","year":"2020","unstructured":"Davila, K., Setlur, S., Doermann, D., Bhargava, U.K., Govindaraju, V.: Chart mining: a survey of methods for automated chart analysis. IEEE Trans. Pattern Anal. Mach. Intell. 43(11), 3799\u20133819 (2020)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"19_CR9","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"361","DOI":"10.1007\/978-3-030-68793-9_27","volume-title":"Pattern Recognition. ICPR International Workshops and Challenges","author":"K Davila","year":"2021","unstructured":"Davila, K., Tensmeyer, C., Shekhar, S., Singh, H., Setlur, S., Govindaraju, V.: ICPR 2020 - competition on harvesting raw tables from infographics. In: Del Bimbo, A., et al. (eds.) ICPR 2021. LNCS, vol. 12668, pp. 361\u2013380. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-68793-9_27"},{"key":"19_CR10","doi-asserted-by":"crossref","unstructured":"Davila, K., et al.: ICDAR 2019 competition on harvesting raw tables from infographics (CHART-Infographics). In: ICDAR. IEEE (2019)","DOI":"10.1109\/ICDAR.2019.00203"},{"key":"19_CR11","doi-asserted-by":"crossref","unstructured":"Davila, K., Xu, F., Ahmed, S., Mendoza, D.A., Setlur, S., Govindaraju, V.: ICPR 2022-challenge on harvesting raw tables from infographics. In: International Conference on Pattern Recognition. IEEE (2022)","DOI":"10.1109\/ICPR56361.2022.9956289"},{"key":"19_CR12","doi-asserted-by":"crossref","unstructured":"Ding, J., Xue, N., Long, Y., Xia, G.S., Lu, Q.: Learning roi transformer for oriented object detection in aerial images. In: CVPR, pp. 2849\u20132858 (2019)","DOI":"10.1109\/CVPR.2019.00296"},{"key":"19_CR13","doi-asserted-by":"crossref","unstructured":"Du, Y., et al.: SVTR: scene text recognition with a single visual model. In: Raedt, L.D. (ed.) International Joint Conference on Artificial Intelligence, pp. 884\u2013890. International Joint Conferences on Artificial Intelligence Organization (July 2022)","DOI":"10.24963\/ijcai.2022\/124"},{"key":"19_CR14","doi-asserted-by":"crossref","unstructured":"Fang, S., Xie, H., Wang, Y., Mao, Z., Zhang, Y.: Abinet: read like humans: autonomous, bidirectional and iterative language modeling for scene text recognition, pp. 7098\u20137107 (2021). https:\/\/arxiv.org\/abs\/2103.06495","DOI":"10.1109\/CVPR46437.2021.00702"},{"key":"19_CR15","doi-asserted-by":"crossref","unstructured":"Han, J., Ding, J., Xue, N., Xia, G.S.: Redet: a rotation-equivariant detector for aerial object detection. In: CVPR, pp. 2786\u20132795 (2021)","DOI":"10.1109\/CVPR46437.2021.00281"},{"key":"19_CR16","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: CVPR, pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"issue":"11","key":"19_CR17","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0241373","volume":"15","author":"LB Hindenes","year":"2020","unstructured":"Hindenes, L.B., H\u00e5berg, A.K., Johnsen, L.H., Mathiesen, E.B., Robben, D., Vangberg, T.R.: Variations in the circle of willis in a large population sample using 3d tof angiography: the troms\u00f8 study. PLoS ONE 15(11), e0241373 (2020)","journal-title":"PLoS ONE"},{"key":"19_CR18","doi-asserted-by":"crossref","unstructured":"Howard, A., et\u00a0al.: Searching for mobilenetv3. In: ICCV, pp. 1314\u20131324 (2019)","DOI":"10.1109\/ICCV.2019.00140"},{"key":"19_CR19","doi-asserted-by":"crossref","unstructured":"Jiang, H., et al.: Reciprocal feature learning via explicit and implicit tasks in scene text recognition (2021). https:\/\/arxiv.org\/abs\/2105.06229","DOI":"10.1007\/978-3-030-86549-8_19"},{"key":"19_CR20","doi-asserted-by":"crossref","unstructured":"Jobin, K., Mondal, A., Jawahar, C.: Docfigure: a dataset for scientific document figure classification. In: ICDARW, vol.\u00a01, pp. 74\u201379. IEEE (2019)","DOI":"10.1109\/ICDARW.2019.00018"},{"key":"19_CR21","unstructured":"Jocher, G., Chaurasia, A., Qiu, J.: Ultralytics YOLO, January 2023. https:\/\/github.com\/ultralytics\/ultralytics"},{"key":"19_CR22","doi-asserted-by":"crossref","unstructured":"Kafle, K., Price, B., Cohen, S., Kanan, C.: Dvqa: understanding data visualizations via question answering. In: CVPR, pp. 5648\u20135656 (2018)","DOI":"10.1109\/CVPR.2018.00592"},{"key":"19_CR23","doi-asserted-by":"crossref","unstructured":"Karatzas, D., et\u00a0al.: ICDAR 2015 competition on robust reading. In: ICDAR, pp. 1156\u20131160. IEEE (2015)","DOI":"10.1109\/ICDAR.2015.7333942"},{"key":"19_CR24","unstructured":"Li, C., et\u00a0al.: PP-OCRV3: more attempts for the improvement of ultra lightweight OCR system. arXiv preprint arXiv:2206.03001 (2022)"},{"key":"19_CR25","unstructured":"Li, H., Wang, P., Shen, C., Zhang, G.: Show, attend and read: a simple and strong baseline for irregular text recognition. ArXiv abs\/1811.00751 (2019)"},{"key":"19_CR26","doi-asserted-by":"crossref","unstructured":"Liao, M., Wan, Z., Yao, C., Chen, K., Bai, X.: Real-time scene text detection with differentiable binarization. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol.\u00a034, pp. 11474\u201311481 (2020)","DOI":"10.1609\/aaai.v34i07.6812"},{"key":"19_CR27","doi-asserted-by":"crossref","unstructured":"Liao, M., Zou, Z., Wan, Z., Yao, C., Bai, X.: Real-time scene text detection with differentiable binarization and adaptive scale fusion. IEEE Trans. Pattern Anal. Mach. Intell. (2022)","DOI":"10.1109\/TPAMI.2022.3155612"},{"key":"19_CR28","unstructured":"Liu, W., Chen, C., Wong, K.Y.K., Su, Z., Han, J.: Star-net: a spatial attention residue network for scene text recognition. In: BMVC, vol.\u00a02, p.\u00a07 (2016)"},{"key":"19_CR29","doi-asserted-by":"crossref","unstructured":"Liu, Z., et al.: Swin transformer: hierarchical vision transformer using shifted windows. In: ICCV (2021)","DOI":"10.1109\/ICCV48922.2021.00986"},{"key":"19_CR30","doi-asserted-by":"crossref","unstructured":"Luo, J., Li, Z., Wang, J., Lin, C.Y.: Chartocr: data extraction from charts images via a deep hybrid framework. In: WACV, pp. 1917\u20131925 (2021)","DOI":"10.1109\/WACV48630.2021.00196"},{"key":"19_CR31","doi-asserted-by":"crossref","unstructured":"Masry, A., Do, X.L., Tan, J.Q., Joty, S., Hoque, E.: ChartQA: a benchmark for question answering about charts with visual and logical reasoning. In: Findings of the ACL, pp. 2263\u20132279. Dublin, Ireland (May 2022)","DOI":"10.18653\/v1\/2022.findings-acl.177"},{"key":"19_CR32","doi-asserted-by":"crossref","unstructured":"Methani, N., Ganguly, P., Khapra, M.M., Kumar, P.: Plotqa: reasoning over scientific plots. In: WACV, pp. 1527\u20131536 (2020)","DOI":"10.1109\/WACV45572.2020.9093523"},{"issue":"4","key":"19_CR33","doi-asserted-by":"publisher","first-page":"729","DOI":"10.1107\/S2052252519007668","volume":"6","author":"JK Park","year":"2019","unstructured":"Park, J.K., et al.: Structures of three ependymin-related proteins suggest their function as a hydrophobic molecule binder. IUCrJ 6(4), 729\u2013739 (2019)","journal-title":"IUCrJ"},{"key":"19_CR34","doi-asserted-by":"crossref","unstructured":"Savva, M., Kong, N., Chhajta, A., Fei-Fei, L., Agrawala, M., Heer, J.: Revision: automated classification, analysis and redesign of chart images. In: ACM Symposium on User Interface Software and Technology, pp. 393\u2013402 (2011)","DOI":"10.1145\/2047196.2047247"},{"issue":"11","key":"19_CR35","doi-asserted-by":"publisher","first-page":"2298","DOI":"10.1109\/TPAMI.2016.2646371","volume":"39","author":"B Shi","year":"2017","unstructured":"Shi, B., Bai, X., Yao, C.: An end-to-end trainable neural network for image-based sequence recognition and its application to scene text recognition. IEEE Trans. Pattern Anal. Mach. Intell. 39(11), 2298\u20132304 (2017)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"19_CR36","doi-asserted-by":"crossref","unstructured":"Siegel, N., Horvitz, Z., Levin, R., Divvala, S., Farhadi, A.: Figureseer: parsing result-figures in research papers. In: ECCV, pp. 664\u2013680. Springer (2016)","DOI":"10.1007\/978-3-319-46478-7_41"},{"key":"19_CR37","doi-asserted-by":"crossref","unstructured":"Szegedy, C., Vanhoucke, V., Ioffe, S., Shlens, J., Wojna, Z.: Rethinking the inception architecture for computer vision. In: CVPR, pp. 2818\u20132826 (2016)","DOI":"10.1109\/CVPR.2016.308"},{"key":"19_CR38","unstructured":"Tan, M., Le, Q.: EfficientNet: rethinking model scaling for convolutional neural networks. In: ICML. PMLR, vol.\u00a097, pp. 6105\u20136114. PMLR, 09\u201315 June 2019"},{"key":"19_CR39","doi-asserted-by":"crossref","unstructured":"Thiyam, J., Singh, S.R., Bora, P.K.: Chart classification: a survey and benchmarking of different state-of-the-art methods. IJDAR 1\u201326 (2023)","DOI":"10.1007\/s10032-023-00443-w"},{"key":"19_CR40","doi-asserted-by":"crossref","unstructured":"Wang, W., et al.: Shape robust text detection with progressive scale expansion network. In: CVPR, pp. 9336\u20139345 (2019)","DOI":"10.1109\/CVPR.2019.00956"},{"key":"19_CR41","doi-asserted-by":"crossref","unstructured":"Wang, Y., Xie, H., Fang, S., Wang, J., Zhu, S., Zhang, Y.: From two to one: a new scene text recognizer with visual language modeling network. In: ICCV, pp. 14194\u201314203 (2021)","DOI":"10.1109\/ICCV48922.2021.01393"},{"key":"19_CR42","doi-asserted-by":"crossref","unstructured":"Yu, D., Li, X., Zhang, C., Han, J., Liu, J., Ding, E.: Towards accurate scene text recognition with semantic reasoning networks. In: CVPR, pp. 12110\u201312119 (2020)","DOI":"10.1109\/CVPR42600.2020.01213"},{"key":"19_CR43","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"135","DOI":"10.1007\/978-3-030-58529-7_9","volume-title":"Computer Vision \u2013 ECCV 2020","author":"X Yue","year":"2020","unstructured":"Yue, X., Kuang, Z., Lin, C., Sun, H., Zhang, W.: RobustScanner: dynamically enhancing positional clues for robust text recognition. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.-M. (eds.) ECCV 2020. LNCS, vol. 12364, pp. 135\u2013151. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58529-7_9"},{"key":"19_CR44","doi-asserted-by":"crossref","unstructured":"Zhou, X., et al.: East: an efficient and accurate scene text detector. In: CVPR, pp. 5551\u20135560 (2017)","DOI":"10.1109\/CVPR.2017.283"},{"key":"19_CR45","doi-asserted-by":"crossref","unstructured":"Zhou, Y., et al.: Mmrotate: a rotated object detection benchmark using pytorch. In: ACM International Conference on Multimedia (2022)","DOI":"10.1145\/3503161.3548541"},{"key":"19_CR46","unstructured":"Zhu, X., Su, W., Lu, L., Li, B., Wang, X., Dai, J.: Deformable DETR: deformable transformers for end-to-end object detection. In: ICLR (2020)"}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-78495-8_19","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,3]],"date-time":"2024-12-03T10:29:32Z","timestamp":1733221772000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-78495-8_19"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,4]]},"ISBN":["9783031784941","9783031784958"],"references-count":46,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-78495-8_19","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,12,4]]},"assertion":[{"value":"4 December 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICPR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Pattern Recognition","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Kolkata","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"India","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"1 December 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 December 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icpr2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/icpr2024.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}