{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T07:33:10Z","timestamp":1767339190713,"version":"build-2065373602"},"reference-count":41,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2023,2,22]],"date-time":"2023-02-22T00:00:00Z","timestamp":1677024000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Text regions in natural scenes have complex and variable shapes. Directly using contour coordinates to describe text regions will make the modeling inadequate and lead to low accuracy of text detection. To address the problem of irregular text regions in natural scenes, we propose an arbitrary-shaped text detection model based on Deformable DETR called BSNet. The model differs from the traditional method of directly predicting contour points by using B-Spline curve to make the text contour more accurate and reduces the number of predicted parameters simultaneously. The proposed model eliminates manually designed components and dramatically simplifies the design. The proposed model achieves F-measure of 86.8% and 87.6% on CTW1500 and Total-Text, demonstrating the model\u2019s effectiveness.<\/jats:p>","DOI":"10.3390\/s23052418","type":"journal-article","created":{"date-parts":[[2023,2,22]],"date-time":"2023-02-22T03:59:16Z","timestamp":1677038356000},"page":"2418","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Arbitrary-Shaped Text Detection with B-Spline Curve Network"],"prefix":"10.3390","volume":"23","author":[{"given":"Yuwei","family":"You","sequence":"first","affiliation":[{"name":"College of Mathematics and Physics, Shanghai University of Electric Power, Shanghai 201306, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuxin","family":"Lei","sequence":"additional","affiliation":[{"name":"College of Foreign Languages, Suzhou University, Suzhou 234000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zixu","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Electronics and Information Engineering, Shanghai University of Electric Power, Shanghai 201306, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2589-5755","authenticated-orcid":false,"given":"Minglei","family":"Tong","sequence":"additional","affiliation":[{"name":"College of Electronics and Information Engineering, Shanghai University of Electric Power, Shanghai 201306, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,2,22]]},"reference":[{"key":"ref_1","unstructured":"Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, \u0141., and Polosukhin, I. 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