{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T14:34:21Z","timestamp":1742913261392,"version":"3.40.3"},"publisher-location":"Cham","reference-count":16,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031425356"},{"type":"electronic","value":"9783031425363"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"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":[[2023]]},"DOI":"10.1007\/978-3-031-42536-3_20","type":"book-chapter","created":{"date-parts":[[2023,8,30]],"date-time":"2023-08-30T18:02:30Z","timestamp":1693418550000},"page":"205-215","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Defect Detection in\u00a0Batavia Woven Fabrics by\u00a0Means of\u00a0Convolutional Neural Networks"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-2988-757X","authenticated-orcid":false,"given":"Nuria","family":"Velasco-P\u00e9rez","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-2602-5773","authenticated-orcid":false,"given":"Samuel","family":"Lozano-Ju\u00e1rez","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-8499-093X","authenticated-orcid":false,"given":"Beatriz","family":"Gil-Arroyo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Juan Marcos","family":"Sanz","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7289-4689","authenticated-orcid":false,"given":"Nu\u00f1o","family":"Basurto","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2662-798X","authenticated-orcid":false,"given":"Daniel","family":"Urda","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2444-5384","authenticated-orcid":false,"given":"\u00c1lvaro","family":"Herrero","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,8,31]]},"reference":[{"key":"20_CR1","unstructured":"Chollet, F., et al.: Keras (2015). https:\/\/keras.io"},{"key":"20_CR2","doi-asserted-by":"crossref","unstructured":"Diez-Olivan, A., Del\u00a0Ser, J., Galar, D., Sierra, B.: Data fusion and machine learning for industrial prognosis: trends and perspectives towards industry 4.0. Inf. Fusion 50, 92\u2013111 (2019)","DOI":"10.1016\/j.inffus.2018.10.005"},{"key":"20_CR3","doi-asserted-by":"crossref","unstructured":"Gao, Y., Gao, L., Li, X.: A hierarchical training-convolutional neural network with feature alignment for steel surface defect recognition. Robot. Comput.-Integr. Manuf. 81, 102507 (2023)","DOI":"10.1016\/j.rcim.2022.102507"},{"key":"20_CR4","doi-asserted-by":"publisher","first-page":"354","DOI":"10.1016\/j.patcog.2017.10.013","volume":"77","author":"J Gu","year":"2018","unstructured":"Gu, J., et al.: Recent advances in convolutional neural networks. Pattern Recogn. 77, 354\u2013377 (2018)","journal-title":"Pattern Recogn."},{"issue":"9\u201310","key":"20_CR5","doi-asserted-by":"publisher","first-page":"971","DOI":"10.1177\/0040517519884124","volume":"90","author":"PR Jeyaraj","year":"2020","unstructured":"Jeyaraj, P.R., Nadar, E.R.S.: Effective textile quality processing and an accurate inspection system using the advanced deep learning technique. Text. Res. J. 90(9\u201310), 971\u2013980 (2020)","journal-title":"Text. Res. J."},{"key":"20_CR6","doi-asserted-by":"crossref","unstructured":"Koulali, I., Eskil, M.T.: Unsupervised textile defect detection using convolutional neural networks. Appl. Soft Comput. 113, 107913 (2021)","DOI":"10.1016\/j.asoc.2021.107913"},{"key":"20_CR7","doi-asserted-by":"crossref","unstructured":"Kovilpillai, J.J.A., Jayanthy, S.: An optimized deep learning approach to detect and classify defective tiles in production line for efficient industrial quality control. Neural Comput. Appl. 1\u201320 (2023)","DOI":"10.1007\/s00521-023-08283-9"},{"issue":"5","key":"20_CR8","first-page":"606","volume":"10","author":"O Ongbali Samson","year":"2019","unstructured":"Ongbali Samson, O., Afolalu Sunday, A., Salawu Enesi, Y.: Bottleneck problems arising in inter-industry production setting and vertical integration: a review. Technology 10(5), 606\u2013612 (2019)","journal-title":"Technology"},{"key":"20_CR9","doi-asserted-by":"crossref","unstructured":"Saberironaghi, A., Ren, J., El-Gindy, M.: Defect detection methods for industrial products using deep learning techniques: a review. Algorithms 16(2) (2023)","DOI":"10.3390\/a16020095"},{"key":"20_CR10","doi-asserted-by":"crossref","unstructured":"Shahrabadi, S., Castilla, Y., Guevara, M., Magalh\u00e3es, L.G., Gonzalez, D., Ad\u00e3o, T.: Defect detection in the textile industry using image-based machine learning methods: a brief review. In: Journal of Physics: Conference Series, vol. 1, p. 012010. IOP Publishing (2022)","DOI":"10.1088\/1742-6596\/2224\/1\/012010"},{"issue":"1","key":"20_CR11","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1007\/s44248-023-00004-w","volume":"1","author":"H Stephani","year":"2023","unstructured":"Stephani, H., Weibel, T., R\u00f6sch, R., Moghiseh, A.: Challenges and approaches when realizing online surface inspection systems with deep learning algorithms. Discov. Data 1(1), 3 (2023)","journal-title":"Discov. Data"},{"key":"20_CR12","doi-asserted-by":"crossref","unstructured":"Tao, X., Zhang, D., Ma, W., Liu, X., Xu, D.: Automatic metallic surface defect detection and recognition with convolutional neural networks. Appl. Sci. 8(9), 1575 (2018)","DOI":"10.3390\/app8091575"},{"key":"20_CR13","doi-asserted-by":"publisher","first-page":"3465","DOI":"10.1007\/s00170-017-0882-0","volume":"94","author":"T Wang","year":"2018","unstructured":"Wang, T., Chen, Y., Qiao, M., Snoussi, H.: A fast and robust convolutional neural network-based defect detection model in product quality control. Int. J. Adv. Manuf. Technol. 94, 3465\u20133471 (2018)","journal-title":"Int. J. Adv. Manuf. Technol."},{"issue":"19\u201320","key":"20_CR14","doi-asserted-by":"publisher","first-page":"3462","DOI":"10.1177\/00405175211073773","volume":"92","author":"B Wei","year":"2022","unstructured":"Wei, B., Xu, B., Hao, K., Gao, L.: Textile defect detection using multilevel and attentional deep learning network (MLMA-Net). Text. Res. J. 92(19\u201320), 3462\u20133477 (2022)","journal-title":"Text. Res. J."},{"key":"20_CR15","doi-asserted-by":"crossref","unstructured":"Zhang, H., Xiong, W., Lu, S., Chen, M., Yao, L.: QA-USTNet: yarn-dyed fabric defect detection via U-shaped swin transformer network based on quadtree attention. Text. Res. J. 00405175231158134 (2023)","DOI":"10.1177\/00405175231158134"},{"issue":"6","key":"20_CR16","doi-asserted-by":"publisher","first-page":"602","DOI":"10.1111\/cote.12624","volume":"138","author":"H Zhang","year":"2022","unstructured":"Zhang, H., Zhang, W., Wang, Y., Lu, S., Yao, L., Chen, X.: Colour-patterned fabric-defect detection using unsupervised and memorial defect-free features. Color. Technol. 138(6), 602\u2013620 (2022)","journal-title":"Color. Technol."}],"container-title":["Lecture Notes in Networks and Systems","18th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2023)"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-42536-3_20","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,30]],"date-time":"2023-08-30T18:05:31Z","timestamp":1693418731000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-42536-3_20"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031425356","9783031425363"],"references-count":16,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-42536-3_20","relation":{},"ISSN":["2367-3370","2367-3389"],"issn-type":[{"type":"print","value":"2367-3370"},{"type":"electronic","value":"2367-3389"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"31 August 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"SOCO","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Soft Computing Models in Industrial and Environmental Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Salamanca","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 September 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7 September 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icscmiea2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/2023.sococonference.eu\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}