{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,2]],"date-time":"2025-08-02T17:22:59Z","timestamp":1754155379236,"version":"3.41.2"},"reference-count":26,"publisher":"Emerald","issue":"5","license":[{"start":{"date-parts":[[2024,4,30]],"date-time":"2024-04-30T00:00:00Z","timestamp":1714435200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IR"],"published-print":{"date-parts":[[2024,9,13]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title>\n<jats:p>This paper aims to estimate contact location from sparse and high-dimensional soft tactile array sensor data using the tactile image. The authors used three feature extraction methods: handcrafted features, convolutional features and autoencoder features. Subsequently, these features were mapped to contact locations through a contact location regression network. Finally, the network performance was evaluated using spherical fittings of three different radii to further determine the optimal feature extraction method.<\/jats:p>\n<\/jats:sec>\n<jats:sec><jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title>\n<jats:p>This paper aims to estimate contact location from sparse and high-dimensional soft tactile array sensor data using the tactile image.<\/jats:p>\n<\/jats:sec>\n<jats:sec><jats:title content-type=\"abstract-subheading\">Findings<\/jats:title>\n<jats:p>This research indicates that data collected by probes can be used for contact localization. Introducing a batch normalization layer after the feature extraction stage significantly enhances the model\u2019s generalization performance. Through qualitative and quantitative analyses, the authors conclude that convolutional methods can more accurately estimate contact locations.<\/jats:p>\n<\/jats:sec>\n<jats:sec><jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title>\n<jats:p>The paper provides both qualitative and quantitative analyses of the performance of three contact localization methods across different datasets. To address the challenge of obtaining accurate contact locations in quantitative analysis, an indirect measurement metric is proposed.<\/jats:p>\n<\/jats:sec>","DOI":"10.1108\/ir-01-2024-0008","type":"journal-article","created":{"date-parts":[[2024,4,28]],"date-time":"2024-04-28T03:13:40Z","timestamp":1714274020000},"page":"789-798","source":"Crossref","is-referenced-by-count":1,"title":["Contact localization from soft tactile array sensor using tactile image"],"prefix":"10.1108","volume":"51","author":[{"given":"Baoxu","family":"Tu","sequence":"first","affiliation":[]},{"given":"Yuanfei","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Kang","family":"Min","sequence":"additional","affiliation":[]},{"given":"Fenglei","family":"Ni","sequence":"additional","affiliation":[]},{"given":"Minghe","family":"Jin","sequence":"additional","affiliation":[]}],"member":"140","published-online":{"date-parts":[[2024,4,30]]},"reference":[{"first-page":"132","article-title":"Learning 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