{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,12]],"date-time":"2026-02-12T09:29:58Z","timestamp":1770888598631,"version":"3.50.1"},"publisher-location":"Cham","reference-count":18,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031500749","type":"print"},{"value":"9783031500756","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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":[[2024]]},"DOI":"10.1007\/978-3-031-50075-6_11","type":"book-chapter","created":{"date-parts":[[2024,1,21]],"date-time":"2024-01-21T06:01:39Z","timestamp":1705816899000},"page":"137-148","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Research on\u00a0Fabric Defect Detection Technology Based on\u00a0RDN-LTE and\u00a0Improved DINO"],"prefix":"10.1007","author":[{"given":"Li","family":"Yao","sequence":"first","affiliation":[]},{"given":"Zhongqin","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Yan","family":"Wan","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,1,22]]},"reference":[{"issue":"1","key":"11_CR1","doi-asserted-by":"publisher","first-page":"79","DOI":"10.13074\/jent.2017.03.171241","volume":"6","author":"SST Selvi","year":"2017","unstructured":"Selvi, S.S.T., Nasira, G.: An effective automatic fabric defect detection system using digital image processing. J. Environ. Nanotechnol. 6(1), 79\u201385 (2017)","journal-title":"J. Environ. Nanotechnol."},{"issue":"9\u201311","key":"11_CR2","doi-asserted-by":"publisher","first-page":"2657","DOI":"10.1007\/s00371-021-02199-y","volume":"37","author":"Z Chen","year":"2021","unstructured":"Chen, Z., Qiu, J., Sheng, B., Li, P., Wu, E.: GPSD: generative parking spot detection using multi-clue recovery model. Vis. Comput. 37(9\u201311), 2657\u20132669 (2021). https:\/\/doi.org\/10.1007\/s00371-021-02199-y","journal-title":"Vis. Comput."},{"issue":"1","key":"11_CR3","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1109\/TII.2021.3085669","volume":"18","author":"J Li","year":"2021","unstructured":"Li, J., et al.: Automatic detection and classification system of domestic waste via multimodel cascaded convolutional neural network. IEEE Trans. Ind. Inf. 18(1), 163\u2013173 (2021)","journal-title":"IEEE Trans. Ind. Inf."},{"issue":"2","key":"11_CR4","doi-asserted-by":"publisher","first-page":"639","DOI":"10.1007\/s00371-020-02040-y","volume":"38","author":"G Liu","year":"2022","unstructured":"Liu, G., Li, F.: Fabric defect detection based on low-rank decomposition with structural constraints. Vis. Comput. 38(2), 639\u2013653 (2022). https:\/\/doi.org\/10.1007\/s00371-020-02040-y","journal-title":"Vis. Comput."},{"key":"11_CR5","doi-asserted-by":"crossref","unstructured":"Xu, Y., Meng, F., Wang, L., Zhang, M., Wu, C.: Fabric surface defect detection based on GMRF model. In: 2021 2nd International Conference on Artificial Intelligence and Information Systems, pp. 1\u20134 (2021)","DOI":"10.1145\/3469213.3471336"},{"key":"11_CR6","series-title":"Lecture Notes in Electrical Engineering","doi-asserted-by":"publisher","first-page":"143","DOI":"10.1007\/978-981-33-6393-9_16","volume-title":"Trends in Wireless Communication and Information Security","author":"S Tola","year":"2021","unstructured":"Tola, S., Sarkar, S., Chandra, J.K., Sarkar, G.: Sparse auto-encoder improvised texture-based statistical feature estimation for the detection of defects in woven fabric. In: Chakraborty, M., Jha, R.K., Balas, V.E., Sur, S.N., Kandar, D. (eds.) Trends in Wireless Communication and Information Security. LNEE, vol. 740, pp. 143\u2013151. Springer, Singapore (2021). https:\/\/doi.org\/10.1007\/978-981-33-6393-9_16"},{"issue":"3","key":"11_CR7","doi-asserted-by":"publisher","first-page":"515","DOI":"10.1007\/s00371-020-01820-w","volume":"37","author":"G Liu","year":"2021","unstructured":"Liu, G., Zheng, X.: Fabric defect detection based on information entropy and frequency domain saliency. Vis. Comput. 37(3), 515\u2013528 (2021). https:\/\/doi.org\/10.1007\/s00371-020-01820-w","journal-title":"Vis. Comput."},{"issue":"9","key":"11_CR8","first-page":"39","volume":"26","author":"X Tang","year":"2018","unstructured":"Tang, X., Huang, K., Qin, Y., Zhou, C.: Fabric defect detection based on Gabor Filter and HOG feature. Comput. Measur. Control 26(9), 39\u201347 (2018)","journal-title":"Comput. Measur. Control"},{"key":"11_CR9","doi-asserted-by":"crossref","unstructured":"Liu, T., Chen, S.: YOLOv4-DCN-based fabric defect detection algorithm. In: 2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC), pp. 710\u2013715. IEEE (2022)","DOI":"10.1109\/YAC57282.2022.10023604"},{"key":"11_CR10","doi-asserted-by":"crossref","unstructured":"Zhao, Z., Gui, K., Wang, P.: Fabric defect detection based on cascade faster R-CNN. In: Proceedings of the 4th International Conference on Computer Science and Application Engineering, pp. 1\u20136 (2020)","DOI":"10.1145\/3424978.3425080"},{"key":"11_CR11","doi-asserted-by":"crossref","unstructured":"Ghiasi, G., et al.: Simple copy-paste is a strong data augmentation method for instance segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 2918\u20132928 (2021)","DOI":"10.1109\/CVPR46437.2021.00294"},{"key":"11_CR12","unstructured":"Zhang, H., et al.: DINO: DETR with improved denoising anchor boxes for end-to-end object detection. In: The Eleventh International Conference on Learning Representations (2022)"},{"key":"11_CR13","doi-asserted-by":"publisher","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 770\u2013778 (2016). https:\/\/doi.org\/10.1109\/CVPR.2016.90","DOI":"10.1109\/CVPR.2016.90"},{"key":"11_CR14","doi-asserted-by":"crossref","unstructured":"Liu, Z., et al.: Swin transformer: hierarchical vision transformer using shifted windows. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 10012\u201310022 (2021)","DOI":"10.1109\/ICCV48922.2021.00986"},{"key":"11_CR15","doi-asserted-by":"crossref","unstructured":"Xia, Z., Pan, X., Song, S., Li, L.E., Huang, G.: Vision transformer with deformable attention. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4794\u20134803 (2022)","DOI":"10.1109\/CVPR52688.2022.00475"},{"key":"11_CR16","doi-asserted-by":"crossref","unstructured":"Kim, J., Lee, J.K., Lee, K.M.: Deeply-recursive convolutional network for image super-resolution. IEEE (2016)","DOI":"10.1109\/CVPR.2016.181"},{"key":"11_CR17","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Tian, Y., Kong, Y., Zhong, B., Fu, Y.: Residual dense network for image super-resolution. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2472\u20132481 (2018)","DOI":"10.1109\/CVPR.2018.00262"},{"key":"11_CR18","doi-asserted-by":"crossref","unstructured":"Lee, J., Jin, K.H.: Local texture estimator for implicit representation function. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 1929\u20131938 (2022)","DOI":"10.1109\/CVPR52688.2022.00197"}],"container-title":["Lecture Notes in Computer Science","Advances in Computer Graphics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-50075-6_11","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,21]],"date-time":"2024-01-21T06:03:52Z","timestamp":1705817032000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-50075-6_11"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031500749","9783031500756"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-50075-6_11","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"22 January 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CGI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Computer Graphics International Conference","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Shanghai","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","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":"28 August 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"1 September 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"cgi2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"385","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"149","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"39% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}