{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T03:17:06Z","timestamp":1774322226753,"version":"3.50.1"},"reference-count":33,"publisher":"Tech Science Press","issue":"1","license":[{"start":{"date-parts":[[2024,10,20]],"date-time":"2024-10-20T00:00:00Z","timestamp":1729382400000},"content-version":"vor","delay-in-days":293,"URL":"https:\/\/doi.org\/10.32604\/TSP-CROSSMARKPOLICY"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["CMC"],"published-print":{"date-parts":[[2024]]},"DOI":"10.32604\/cmc.2024.055893","type":"journal-article","created":{"date-parts":[[2024,9,25]],"date-time":"2024-09-25T20:40:12Z","timestamp":1727296812000},"page":"1197-1214","update-policy":"https:\/\/doi.org\/10.32604\/tsp-crossmarkpolicy","source":"Crossref","is-referenced-by-count":2,"title":["Industrial Fusion Cascade Detection of Solder Joint"],"prefix":"10.32604","volume":"81","author":[{"given":"Chunyuan","family":"Li","sequence":"first","affiliation":[]},{"given":"Peng","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Shuangming","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Lie","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Mingquan","family":"Shi","sequence":"additional","affiliation":[]}],"member":"17807","published-online":{"date-parts":[[2024]]},"reference":[{"key":"ref1","first-page":"50","article-title":"Review of 3D machine vision development and its industrial application","volume":"4","author":"Ma","year":"2022","journal-title":"Micro\/nano Electron. Intell. Manuf."},{"key":"ref2","first-page":"1135","article-title":"Learning both weights and connections for efficient neural network","volume":"5","author":"Han","year":"2015","journal-title":"Neural Evol. Comput."},{"key":"ref3","first-page":"2980","article-title":"Mask R-CNN","volume":"42","author":"He","year":"2017","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref4","first-page":"1440","article-title":"Fast R-CNN","author":"Girshick","year":"2015","journal-title":"Comput. Sci."},{"key":"ref5","doi-asserted-by":"crossref","first-page":"1137","DOI":"10.1109\/TPAMI.2016.2577031","article-title":"Faster R-CNN: Towards real-time object detection with region proposal networks","volume":"39","author":"Ren","year":"2017","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref6","series-title":"2018 IEEE\/CVF Conf. Comput. Vis. Pattern Recognit.","first-page":"6154","article-title":"Cascade R-CNN: Delving into high quality object detection","author":"Cai","year":"2018"},{"key":"ref7","unstructured":"Z. Ge, S. Liu, F. Wang, Z. Li, and J. Sun, \u201cYOLOX: Exceeding YOLO series in 2021,\u201d 2021. doi: 10.48550\/arXiv.2107.08430."},{"key":"ref8","doi-asserted-by":"crossref","unstructured":"C. Y. Wang, I. H. Yeh, and H. Y. M. Liao, \u201cYOLOv9: Learning what you want to learn using programmable gradient information,\u201d 2024. doi: 10.48550\/arXiv.2402.13616.","DOI":"10.1007\/978-3-031-72751-1_1"},{"key":"ref9","series-title":"2021 IEEE 11th Annual Int. Conf. CYBER Technol. Autom., Control, Intell. Syst. (CYBER)","first-page":"704","article-title":"Application of YOLO object detection network in weld surface defect detection","author":"Zuo","year":"2021"},{"key":"ref10","doi-asserted-by":"crossref","first-page":"1629","DOI":"10.1007\/s10845-023-02124-1","article-title":"Automatic quality control of aluminium parts welds based on 3D data and artificial intelligence","volume":"35","author":"Cardellicchio","year":"2024","journal-title":"J. Intell. Manuf."},{"key":"ref11","series-title":"Proc. IEEE\/CVF Conf. Comput. Vis. Pattern Recognit.","first-page":"3588","article-title":"Relation networks for objectdetection","author":"Hu","year":"Jun. 2018"},{"key":"ref12","unstructured":"A. Vaswani et al., \u201cAttention is all you need,\u201d 2017. doi: 10.48550\/arXiv.1706.03762."},{"key":"ref13","doi-asserted-by":"crossref","first-page":"1726","DOI":"10.1109\/TIP.2023.3251693","article-title":"Rethinking attentive object detection via neural attention learning","volume":"33","author":"Ge","year":"2024","journal-title":"IEEE Trans. Image Process."},{"key":"ref14","first-page":"75","article-title":"Research on automotive weld inspection systembased on machine vision","volume":"41","author":"Han","year":"2018","journal-title":"J. Changchun Univ. Sci. Technol. (Nat. Sci. Ed.)"},{"key":"ref15","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1134\/S1061830923700262","article-title":"Ultrasonic inspection technique for welded joints obtained by spot friction stir welding","volume":"59","author":"Borovkov","year":"2023","journal-title":"Russ. J. Nondestruct. Test."},{"key":"ref16","first-page":"31","article-title":"Research on detection of automobile components solder joint quality,computer measurement & control","volume":"22","author":"Lin","year":"2014","journal-title":"Comput. Meas. Control,"},{"key":"ref17","first-page":"33","article-title":"Welding spot positioning method for body-in-white based on lightweight YOLOv7","volume":"4","author":"Xie","year":"2023","journal-title":"Veh. Power Technol."},{"key":"ref18","unstructured":"X. Chen and A. Gupta, \u201cAn implementation of faster RCNN with study for region sampling,\u201d 2017. doi: 10.48550\/arXiv.1702.02138."},{"key":"ref19","first-page":"812","article-title":"Small targets detection for transmission tower based on SRGAN and faster RCNN","volume":"8","author":"Liu","year":"2021","journal-title":"Recent Adv. Electr. Electron. Eng."},{"key":"ref20","first-page":"12","article-title":"Image registration by feature based information fusion","volume":"2","author":"Narani","year":"2012","journal-title":"Found. Comput. Sci. (FCS)"},{"key":"ref21","first-page":"281","article-title":"Image matching based on multi-features fusion","volume":"16","author":"Peng","year":"2004","journal-title":"High Power Laser Part. Beams"},{"key":"ref22","first-page":"1325","article-title":"Object detection and recognition based on multiscale deformable template","volume":"39","author":"Yu","year":"2002","journal-title":"J. Comput. Res. Dev."},{"key":"ref23","first-page":"1","article-title":"Feature pyramid networks for object detection","author":"Lin","year":"2017","journal-title":"Comput. Vis. Pattern Recognit."},{"key":"ref24","first-page":"770","article-title":"Deep residual learning for image recognition","volume":"1","author":"He","year":"2016","journal-title":"IEEE"},{"key":"ref25","first-page":"10915","article-title":"Knowledge distillation: A good teacher is patient and consistent","volume":"1","author":"Beyer","year":"2021","journal-title":"IEEE\/CVF Conf. Comput. Vis. Pattern Recognit."},{"key":"ref26","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1016\/j.patcog.2021.108023","article-title":"EFNet: Enhancement-fusion network for semantic segmentation","volume":"118","author":"Wang","year":"2021","journal-title":"Pattern Recognit.: J. Pattern Recognit. Soc."},{"key":"ref27","doi-asserted-by":"crossref","first-page":"1369","DOI":"10.1016\/S0031-3203(02)00262-5","volume":"36","author":"Yang","year":"2003","journal-title":"Pattern Recognit."},{"key":"ref28","first-page":"1","article-title":"Improved YOLOv5 based on feature fusion and attention mechanism and its application in continuous casting slab detection","volume":"72","author":"Yang","year":"2023","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref29","doi-asserted-by":"crossref","first-page":"31","DOI":"10.3390\/s23167027","article-title":"A novel decoupled feature pyramid networks for multi-target ship detection","volume":"23","author":"Xue","year":"2023","journal-title":"Sensors"},{"key":"ref30","series-title":"Int. Symp. Artif. Intell. Robot.","article-title":"Cross-layer feature attention module for multi-scale object detection","author":"Zheng","year":"2022"},{"key":"ref31","doi-asserted-by":"crossref","first-page":"3511","DOI":"10.1007\/s10489-021-02534-9","article-title":"Multi-scale object detection for high-speed railway clearance intrusion","volume":"52","author":"Tian","year":"2022","journal-title":"Appl. Intell.: Int. J. Artif. Intell., Neural Netw., Complex Problem-Solving Technol."},{"key":"ref32","doi-asserted-by":"crossref","first-page":"4277","DOI":"10.1049\/gtd2.12948","article-title":"An improved cascade RCNN detection method for key components and defects of transmission lines","volume":"17","author":"Dong","year":"2023","journal-title":"IET Gener., Transm. Dis."},{"key":"ref33","doi-asserted-by":"crossref","first-page":"834","DOI":"10.1007\/978-3-030-80119-9_54","volume":"283","author":"Li","year":"2022","journal-title":"Intelligent Computing"}],"container-title":["Computers, Materials & Continua"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.techscience.com\/files\/cmc\/2024\/TSP_CMC-81-1\/TSP_CMC_55893\/TSP_CMC_55893.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,7]],"date-time":"2025-03-07T02:42:34Z","timestamp":1741315354000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.techscience.com\/cmc\/v81n1\/58353"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"references-count":33,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2024]]},"published-print":{"date-parts":[[2024]]}},"URL":"https:\/\/doi.org\/10.32604\/cmc.2024.055893","relation":{},"ISSN":["1546-2226"],"issn-type":[{"value":"1546-2226","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"2024-07-09","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2024-09-09","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2024-10-15","order":2,"name":"published","label":"Published Online","group":{"name":"publication_history","label":"Publication History"}}]}}