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Due to the unique functionalities of mechanoreceptors in human skin, humans can easily distinguish materials with different surface characteristics (e.g., compressibility, roughness, etc.) by simply pressing and sliding the fingertip over the samples. However, how to achieve such delicate texture recognition for robots remains an open challenge due to the lack of skin\u2010comparable tactile sensing systems and smart pattern recognition algorithms. Herein, a novel texture recognition method is proposed by designing an arc\u2010shaped soft tactile sensor and a bidirectional long short\u2010term memory (LSTM) model with the attention mechanism. By using the proposed method, a respective recognition accuracy of 97% for Braille characters and 99% for 60 types of fabrics have been achieved, revealing the effectiveness of our method in surface texture recognition and the potential benefit to various applications, such as Braille reading for visually impaired people and defect detection in the textile industry.<\/jats:p><\/jats:sec>","DOI":"10.1002\/aisy.202100076","type":"journal-article","created":{"date-parts":[[2021,8,21]],"date-time":"2021-08-21T16:45:25Z","timestamp":1629564325000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":61,"title":["Surface Texture Recognition by Deep Learning\u2010Enhanced Tactile Sensing"],"prefix":"10.1002","volume":"4","author":[{"given":"Youcan","family":"Yan","sequence":"first","affiliation":[{"name":"Department of Biomedical Engineering City University of Hong Kong  Tat Chee Avenue Kowloon Hong Kong China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhe","family":"Hu","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering City University of Hong Kong  Tat Chee Avenue Kowloon Hong Kong China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yajing","family":"Shen","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering City University of Hong Kong  Tat Chee Avenue Kowloon Hong Kong China"},{"name":"Shenzhen Research Institute City University of Hong Kong  Shenzhen 518057 China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9003-2054","authenticated-orcid":false,"given":"Jia","family":"Pan","sequence":"additional","affiliation":[{"name":"Department of Computer Science University of Hong Kong  Pokfulam Hong Kong China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2021,8,21]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1002\/vis.245"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.imavis.2011.02.002"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.3390\/s20051459"},{"key":"e_1_2_8_5_1","doi-asserted-by":"publisher","DOI":"10.1177\/0278364917700714"},{"key":"e_1_2_8_6_1","volume":"36","author":"Shih B.","year":"2020","journal-title":"Sci. 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