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However, recent methods have not taken advantage of structure information effectively, resulting in low accuracy when dealing with crack-like noises. In this paper, we propose a novel crack detection framework, which is able to identify cracks from noisy background. The main contributions of this paper are as follows: (1) giving a new edge-based crack detection framework to improve the detection performance; (2) proposing a novel mid-level feature, named\n                    <jats:italic>Crack Token<\/jats:italic>\n                    , which captures the local structure information of cracks; (3) introducing a new evaluation strategy for crack detection task, which provides a comprehensive system for approach evaluation and comparison in this area. In addition, we provide a novel definition of pavement crack and verify our framework and evaluation strategy in this real world application. Extensive experiments demonstrate the state-of-the-art results of the proposed framework.\n                  <\/jats:p>","DOI":"10.3233\/jifs-190868","type":"journal-article","created":{"date-parts":[[2019,12,31]],"date-time":"2019-12-31T07:39:40Z","timestamp":1577777980000},"page":"3501-3513","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":6,"title":["Token based crack detection"],"prefix":"10.1177","volume":"38","author":[{"given":"Fan","family":"Meng","sequence":"first","affiliation":[{"name":"School of Management Science and Engineering, Central University of Finance and Economics, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhiquan","family":"Qi","sequence":"additional","affiliation":[{"name":"School of Ecomonics and Management, University of Chinese Academy of Sciences, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhensong","family":"Chen","sequence":"additional","affiliation":[{"name":"Information School, Capital University of Economics and Business, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bo","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Information Technology and Management, University of International Business and Economics, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yong","family":"Shi","sequence":"additional","affiliation":[{"name":"School of Ecomonics and Management, University of Chinese Academy of Sciences, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2019,12,29]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2010.161"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1155\/2008\/861701"},{"key":"e_1_3_2_4_2","first-page":"4380","article-title":"Deepedge: A multi-scale bifurcated deep network for topdown contour detection","author":"Bertasius G.","year":"2015","unstructured":"BertasiusG., ShiJ. and TorresaniL., Deepedge: A multi-scale bifurcated deep network for topdown contour detection. 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