{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T21:40:26Z","timestamp":1783114826663,"version":"3.54.6"},"reference-count":54,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2024,2,3]],"date-time":"2024-02-03T00:00:00Z","timestamp":1706918400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61602157"],"award-info":[{"award-number":["61602157"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["202102210167"],"award-info":[{"award-number":["202102210167"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Henan Science and Technology Planning Program","award":["61602157"],"award-info":[{"award-number":["61602157"]}]},{"name":"Henan Science and Technology Planning Program","award":["202102210167"],"award-info":[{"award-number":["202102210167"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In recent years, significant progress has been witnessed in the field of deep learning-based object detection. As a subtask in the field of object detection, traffic sign detection has great potential for development. However, the existing object detection methods for traffic sign detection in real-world scenes are plagued by issues such as the omission of small objects and low detection accuracies. To address these issues, a traffic sign detection model named YOLOv7-Traffic Sign (YOLOv7-TS) is proposed based on sub-pixel convolution and feature fusion. Firstly, the up-sampling capability of the sub-pixel convolution integrating channel dimension is harnessed and a Feature Map Extraction Module (FMEM) is devised to mitigate the channel information loss. Furthermore, a Multi-feature Interactive Fusion Network (MIFNet) is constructed to facilitate enhanced information interaction among all feature layers, improving the feature fusion effectiveness and strengthening the perception ability of small objects. Moreover, a Deep Feature Enhancement Module (DFEM) is established to accelerate the pooling process while enriching the highest-layer feature. YOLOv7-TS is evaluated on two traffic sign datasets, namely CCTSDB2021 and TT100K. Compared with YOLOv7, YOLOv7-TS, with a smaller number of parameters, achieves a significant enhancement of 3.63% and 2.68% in the mean Average Precision (mAP) for each respective dataset, proving the effectiveness of the proposed model.<\/jats:p>","DOI":"10.3390\/s24030989","type":"journal-article","created":{"date-parts":[[2024,2,6]],"date-time":"2024-02-06T12:38:24Z","timestamp":1707223104000},"page":"989","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["YOLOv7-TS: A Traffic Sign Detection Model Based on Sub-Pixel Convolution and Feature Fusion"],"prefix":"10.3390","volume":"24","author":[{"given":"Shan","family":"Zhao","sequence":"first","affiliation":[{"name":"School of Software, Henan Polytechnic University, Jiaozuo 454000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yang","family":"Yuan","sequence":"additional","affiliation":[{"name":"School of Software, Henan Polytechnic University, Jiaozuo 454000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xuan","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Software, Henan Polytechnic University, Jiaozuo 454000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yunlei","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Software, Henan Polytechnic University, Jiaozuo 454000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fukai","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Software, Henan Polytechnic University, Jiaozuo 454000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,2,3]]},"reference":[{"key":"ref_1","unstructured":"Benallal, M., and Meunier, J. 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