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However, the computation cost of convolution neural networks (CNNs)-based models is very high. This research proposed an involution-enabled Faster R-CNN network by using the bottleneck structure of the residual network. The involution has two advantages over convolution: first, it can capture a larger range of receptive fields in the spatial dimension; then, parameters are shared in the channel dimension to reduce information redundancy, thus reducing parameters and computation. The detection performance is evaluated by Params, floating-point operations per second (FLOPs), and average precision (AP) in the collected dataset containing 6308 defective fabric images. The experiment results demonstrate that the proposed involution-based network achieves a lighter model, with Params reduced to 31.21 M and FLOPs decreased to 176.19 G, compared to the Faster R-CNN\u2019s 41.14 M Params and 206.68 G FLOPs. Additionally, it slightly improves the detection effect of large defects, increasing the AP value from 50.5% to 51.1%. The findings of this research could offer a promising solution for efficient fabric defect detection in practical textile manufacturing.<\/jats:p>","DOI":"10.3390\/info16050340","type":"journal-article","created":{"date-parts":[[2025,4,23]],"date-time":"2025-04-23T06:38:37Z","timestamp":1745390317000},"page":"340","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Novel Involution-Based Lightweight Network for Fabric Defect Detection"],"prefix":"10.3390","volume":"16","author":[{"given":"Zhenxia","family":"Ke","sequence":"first","affiliation":[{"name":"School of Textile, Apparel & Art Design, Shaoxing University Yuanpei College, Shaoxing 312000, China"},{"name":"School of Textile Science and Engineering, Xi\u2019an Polytechnic University, Xi\u2019an 710048, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4101-5885","authenticated-orcid":false,"given":"Lingjie","family":"Yu","sequence":"additional","affiliation":[{"name":"School of Textile Science and Engineering, Xi\u2019an Polytechnic University, Xi\u2019an 710048, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chao","family":"Zhi","sequence":"additional","affiliation":[{"name":"School of Textile Science and Engineering, Xi\u2019an Polytechnic University, Xi\u2019an 710048, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tao","family":"Xue","sequence":"additional","affiliation":[{"name":"School of Textile Science and Engineering, Xi\u2019an Polytechnic University, Xi\u2019an 710048, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuming","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Textile, Apparel & Art Design, Shaoxing University Yuanpei College, Shaoxing 312000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,4,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"431","DOI":"10.1080\/00405009208631217","article-title":"FDAS: A knowledge-based framework for analysis of defects in woven textile structures","volume":"83","author":"Srinivasan","year":"1990","journal-title":"J. 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