{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T04:10:03Z","timestamp":1742962203899,"version":"3.40.3"},"publisher-location":"Cham","reference-count":34,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031781186"},{"type":"electronic","value":"9783031781193"}],"license":[{"start":{"date-parts":[[2024,12,5]],"date-time":"2024-12-05T00:00:00Z","timestamp":1733356800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,12,5]],"date-time":"2024-12-05T00:00:00Z","timestamp":1733356800000},"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\/978-3-031-78119-3_20","type":"book-chapter","created":{"date-parts":[[2024,12,4]],"date-time":"2024-12-04T01:59:58Z","timestamp":1733277598000},"page":"287-302","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["OCR4HSV: A Multi-task Learning Approach for\u00a0Handwritten Signature Verification"],"prefix":"10.1007","author":[{"given":"Chao-Qun","family":"Lin","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Da-Han","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yan-Fei","family":"Su","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"De-Wu","family":"Ge","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xu-Yao","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,12,5]]},"reference":[{"key":"20_CR1","doi-asserted-by":"crossref","unstructured":"Chaudhuri, A., et al.: Optical Character Recognition Systems. Springer (2017)","DOI":"10.1007\/978-3-319-50252-6_2"},{"key":"20_CR2","unstructured":"Dey, S., Dutta, A., Toledo, J.I., Ghosh, S.K., Llad\u00f3s, J., Pal, U.: Signet: convolutional siamese network for writer independent offline signature verification. arXiv preprint arXiv:1707.02131 (2017)"},{"key":"20_CR3","doi-asserted-by":"crossref","unstructured":"Dhavale, S.V.: Advanced Image-Based Spam Detection and Filtering Techniques. IGI Global (2017)","DOI":"10.4018\/978-1-68318-013-5"},{"key":"20_CR4","unstructured":"Dosovitskiy, A., et al.: An image is worth 16x16 words: transformers for image recognition at scale. arXiv preprint arXiv:2010.11929 (2020)"},{"key":"20_CR5","doi-asserted-by":"crossref","unstructured":"Fang, S., Xie, H., Wang, Y., Mao, Z., Zhang, Y.: Read like humans: autonomous, bidirectional and iterative language modeling for scene text recognition. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 7098\u20137107 (2021)","DOI":"10.1109\/CVPR46437.2021.00702"},{"key":"20_CR6","doi-asserted-by":"crossref","unstructured":"Graves, A., Fern\u00e1ndez, S., Gomez, F., Schmidhuber, J.: Connectionist temporal classification: labelling unsegmented sequence data with recurrent neural networks. In: Proceedings of the 23rd International Conference on Machine Learning, pp. 369\u2013376 (2006)","DOI":"10.1145\/1143844.1143891"},{"key":"20_CR7","unstructured":"Gu, A.: Modeling Sequences with Structured State Spaces. Stanford University (2023)"},{"key":"20_CR8","unstructured":"Gu, A., Dao, T.: Mamba: linear-time sequence modeling with selective state spaces. arXiv preprint arXiv:2312.00752 (2023)"},{"key":"20_CR9","unstructured":"Gu, A., Goel, K., R\u00e9, C.: Efficiently modeling long sequences with structured state spaces. arXiv preprint arXiv:2111.00396 (2021)"},{"issue":"1","key":"20_CR10","doi-asserted-by":"publisher","first-page":"103","DOI":"10.1016\/j.patcog.2014.07.016","volume":"48","author":"Y Guerbai","year":"2015","unstructured":"Guerbai, Y., Chibani, Y., Hadjadji, B.: The effective use of the one-class svm classifier for handwritten signature verification based on writer-independent parameters. Pattern Recogn. 48(1), 103\u2013113 (2015)","journal-title":"Pattern Recogn."},{"key":"20_CR11","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1016\/j.patcog.2017.05.012","volume":"70","author":"LG Hafemann","year":"2017","unstructured":"Hafemann, L.G., Sabourin, R., Oliveira, L.S.: Learning features for offline handwritten signature verification using deep convolutional neural networks. Pattern Recogn. 70, 163\u2013176 (2017)","journal-title":"Pattern Recogn."},{"key":"20_CR12","unstructured":"Huang, F.H., Lu, H.M.: Multiscale feature learning using co-tuplet loss for offline handwritten signature verification. Available at SSRN 4677183"},{"key":"20_CR13","doi-asserted-by":"crossref","unstructured":"Huang, Z., Wang, X., Huang, L., Huang, C., Wei, Y., Liu, W.: Ccnet: criss-cross attention for semantic segmentation. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 603\u2013612 (2019)","DOI":"10.1109\/ICCV.2019.00069"},{"key":"20_CR14","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s11263-015-0823-z","volume":"116","author":"M Jaderberg","year":"2016","unstructured":"Jaderberg, M., Simonyan, K., Vedaldi, A., Zisserman, A.: Reading text in the wild with convolutional neural networks. Int. J. Comput. Vision 116, 1\u201320 (2016)","journal-title":"Int. J. Comput. Vision"},{"key":"20_CR15","doi-asserted-by":"crossref","unstructured":"Li, C., Lin, F., Wang, Z., Yu, G., Yuan, L., Wang, H.: Deephsv: user-independent offline signature verification using two-channel CNN. In: 2019 International Conference on Document Analysis and Recognition (ICDAR), pp. 166\u2013171. IEEE (2019)","DOI":"10.1109\/ICDAR.2019.00035"},{"key":"20_CR16","doi-asserted-by":"crossref","unstructured":"Li, H., Wei, P., Hu, P.: Static-dynamic interaction networks for offline signature verification. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol.\u00a035, pp. 1893\u20131901 (2021)","DOI":"10.1609\/aaai.v35i3.16284"},{"key":"20_CR17","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2023.109882","volume":"145","author":"H Li","year":"2024","unstructured":"Li, H., Wei, P., Ma, Z., Li, C., Zheng, N.: Transosv: offline signature verification with transformers. Pattern Recogn. 145, 109882 (2024)","journal-title":"Pattern Recogn."},{"key":"20_CR18","doi-asserted-by":"crossref","unstructured":"Li, M., et al.: Trocr: transformer-based optical character recognition with pre-trained models. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol.\u00a037, pp. 13094\u201313102 (2023)","DOI":"10.1609\/aaai.v37i11.26538"},{"key":"20_CR19","doi-asserted-by":"crossref","unstructured":"Liang, X., Niu, M., Han, J., Xu, H., Xu, C., Liang, X.: Visual exemplar driven task-prompting for unified perception in autonomous driving. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 9611\u20139621 (2023)","DOI":"10.1109\/CVPR52729.2023.00927"},{"key":"20_CR20","doi-asserted-by":"publisher","unstructured":"Lin, C., et al.: Offline handwriting verification based on siamese network and multi-channel fusion. Acta Automat. Sinica 50(AAS-CN-2023-0777), 1 (2024). https:\/\/doi.org\/10.16383\/j.aas.c230777","DOI":"10.16383\/j.aas.c230777"},{"key":"20_CR21","doi-asserted-by":"crossref","unstructured":"Lin, T.Y., Goyal, P., Girshick, R., He, K., Doll\u00e1r, P.: Focal loss for dense object detection. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 2980\u20132988 (2017)","DOI":"10.1109\/ICCV.2017.324"},{"key":"20_CR22","unstructured":"Liu, C., Liu, Y., Dai, R.: Writer identification by multichannel decomposition and matching (1997). http:\/\/www.aas.net.cn\/article\/id\/17080"},{"key":"20_CR23","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2021.108009","volume":"118","author":"L Liu","year":"2021","unstructured":"Liu, L., Huang, L., Yin, F., Chen, Y.: Offline signature verification using a region based deep metric learning network. Pattern Recogn. 118, 108009 (2021)","journal-title":"Pattern Recogn."},{"key":"20_CR24","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2022.105639","volume":"118","author":"JX Ren","year":"2023","unstructured":"Ren, J.X., Xiong, Y.J., Zhan, H., Huang, B.: 2c2s: a two-channel and two-stream transformer based framework for offline signature verification. Eng. Appl. Artif. Intell. 118, 105639 (2023)","journal-title":"Eng. Appl. Artif. Intell."},{"key":"20_CR25","doi-asserted-by":"crossref","unstructured":"Ren, X., Lai, S., et\u00a0al.: Medical image enhancement based on laplace transform, sobel operator and histogram equalization. Acad. J. Comput. Inf. Sci. 5(6) (2022)","DOI":"10.25236\/AJCIS.2022.050608"},{"key":"20_CR26","first-page":"21031","volume":"34","author":"J Shen","year":"2021","unstructured":"Shen, J., Zhen, X., Worring, M., Shao, L.: Variational multi-task learning with gumbel-softmax priors. Adv. Neural. Inf. Process. Syst. 34, 21031\u201321042 (2021)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"issue":"11","key":"20_CR27","doi-asserted-by":"publisher","first-page":"2298","DOI":"10.1109\/TPAMI.2016.2646371","volume":"39","author":"B Shi","year":"2016","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 (2016)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"20_CR28","doi-asserted-by":"crossref","unstructured":"Wei, P., Li, H., Hu, P.: Inverse discriminative networks for handwritten signature verification. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5764\u20135772 (2019)","DOI":"10.1109\/CVPR.2019.00591"},{"key":"20_CR29","doi-asserted-by":"crossref","unstructured":"Xin, Y., Du, J., Wang, Q., Lin, Z., Yan, K.: Vmt-adapter: parameter-efficient transfer learning for multi-task dense scene understanding. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol.\u00a038, pp. 16085\u201316093 (2024)","DOI":"10.1609\/aaai.v38i14.29541"},{"key":"20_CR30","unstructured":"Xu, Y., et al.: Layoutxlm: multimodal pre-training for multilingual visually-rich document understanding. arXiv preprint arXiv:2104.08836 (2021)"},{"key":"20_CR31","doi-asserted-by":"publisher","unstructured":"Yan, K., et al.: Signature detection, restoration, and verification: a novel chinese document signature forgery detection benchmark. In: 2022 IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). IEEE (2022). https:\/\/doi.org\/10.1109\/cvprw56347.2022.00564","DOI":"10.1109\/cvprw56347.2022.00564"},{"key":"20_CR32","doi-asserted-by":"crossref","unstructured":"Yang, E., et al.: Adatask: a task-aware adaptive learning rate approach to multi-task learning. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol.\u00a037, pp. 10745\u201310753 (2023)","DOI":"10.1609\/aaai.v37i9.26275"},{"key":"20_CR33","doi-asserted-by":"crossref","unstructured":"Yang, Z., et al.: Focal and global knowledge distillation for detectors. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4643\u20134652 (2022)","DOI":"10.1109\/CVPR52688.2022.00460"},{"key":"20_CR34","doi-asserted-by":"crossref","unstructured":"Zhong, X., ShafieiBavani, E., Jimeno\u00a0Yepes, A.: Image-based table recognition: data, model, and evaluation. In: European Conference on Computer Vision, pp. 564\u2013580. Springer (2020)","DOI":"10.1007\/978-3-030-58589-1_34"}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-78119-3_20","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,4]],"date-time":"2024-12-04T02:06:33Z","timestamp":1733277993000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-78119-3_20"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,5]]},"ISBN":["9783031781186","9783031781193"],"references-count":34,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-78119-3_20","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024,12,5]]},"assertion":[{"value":"5 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"}}]}}