{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T11:26:39Z","timestamp":1783596399284,"version":"3.55.0"},"reference-count":68,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Neurocomputing"],"published-print":{"date-parts":[[2026,10]]},"DOI":"10.1016\/j.neucom.2026.134412","type":"journal-article","created":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T16:36:00Z","timestamp":1782923760000},"page":"134412","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["SHMNet: A lightweight backbone network with an auxiliary branch for blister pharmaceutical detection"],"prefix":"10.1016","volume":"699","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-8726-6525","authenticated-orcid":false,"given":"Gaowei","family":"Wang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9659-0452","authenticated-orcid":false,"given":"Jianping","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-9020-1146","authenticated-orcid":false,"given":"Chen","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-3080-0867","authenticated-orcid":false,"given":"Houping","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-4877-8345","authenticated-orcid":false,"given":"Fajia","family":"Wan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.neucom.2026.134412_bib0005","series-title":"Quality Assurance of Pharmaceuticals: A Compendium of Guidelines and Related Materials, Volume 1. Good Practices and Related Regulatory Guidance","year":"2024"},{"key":"10.1016\/j.neucom.2026.134412_bib0010","doi-asserted-by":"crossref","first-page":"250","DOI":"10.1007\/s44196-025-00986-2","article-title":"Pharmanet deep: real-time pharmaceutical defect detection using defect-guided feature fusion and uncertainty-driven inspection","volume":"18","author":"Vijayakumar","year":"2025","journal-title":"Int. J. Comput. Intell. Syst."},{"key":"10.1016\/j.neucom.2026.134412_bib0015","series-title":"2023 5th International Conference on Electronics and Communication, Network and Computer Technology (ECNCT)","first-page":"246","article-title":"Capsule defect detection method based on improved faster RCNN","author":"Zhang","year":"2023"},{"key":"10.1016\/j.neucom.2026.134412_bib0020","doi-asserted-by":"crossref","first-page":"429","DOI":"10.3390\/a17100429","article-title":"Improved U2Net-based surface defect detection method for blister tablets","volume":"17","author":"Zhou","year":"2024","journal-title":"Algorithms"},{"key":"10.1016\/j.neucom.2026.134412_bib0025","doi-asserted-by":"crossref","first-page":"5254","DOI":"10.3390\/s25175254","article-title":"Unsupervised tablet defect detection method based on diffusion model","volume":"25","author":"Zhang","year":"2025","journal-title":"Sensors"},{"key":"10.1016\/j.neucom.2026.134412_bib0030","doi-asserted-by":"crossref","DOI":"10.1007\/s10462-025-11439-9","article-title":"Reinforcement learning for single-agent to multi-agent systems: from basic theory to industrial application progress, a survey","author":"Zhang","year":"2025","journal-title":"Artif. Intell. Rev."},{"key":"10.1016\/j.neucom.2026.134412_bib0035","series-title":"Proceedings of the IEEE International Conference on Computer Vision (ICCV)","article-title":"Focal loss for dense object detection","author":"Lin","year":"2017"},{"key":"10.1016\/j.neucom.2026.134412_bib0040","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","article-title":"You only look once: unified, real-time object detection","author":"Redmon","year":"2016"},{"key":"10.1016\/j.neucom.2026.134412_bib0045","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2024.123199","article-title":"A real-time anchor-free defect detector with global and local feature enhancement for surface defect detection","volume":"246","author":"Liu","year":"2024","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.neucom.2026.134412_bib0050","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"4497","article-title":"MobileMamba: lightweight multi-receptive visual Mamba network","author":"He","year":"2025"},{"key":"10.1016\/j.neucom.2026.134412_bib0055","first-page":"1","article-title":"MFNet: a novel multilevel feature fusion network with multibranch structure for surface defect detection","volume":"72","author":"Zhu","year":"2023","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"10.1016\/j.neucom.2026.134412_bib0060","doi-asserted-by":"crossref","first-page":"42327","DOI":"10.1109\/JSEN.2024.3483278","article-title":"An auxiliary branch semisupervised domain generalization network for unseen working conditions bearing fault diagnosis","volume":"24","author":"Zeng","year":"2024","journal-title":"IEEE Sens. J."},{"key":"10.1016\/j.neucom.2026.134412_bib0065","series-title":"2023 5th International Conference on Communications, Information System and Computer Engineering (CISCE)","first-page":"382","article-title":"Aux-ViT: classification of Alzheimer\u2019s disease from MRI based on vision transformer with auxiliary branch","author":"Duan","year":"2023"},{"key":"10.1016\/j.neucom.2026.134412_bib0070","series-title":"Computer Vision \u2013 ECCV 2024","first-page":"1","article-title":"YOLOv9: learning what you want to learn using programmable gradient information","author":"Wang","year":"2025"},{"key":"10.1016\/j.neucom.2026.134412_bib0075","doi-asserted-by":"crossref","first-page":"5818","DOI":"10.1109\/TNNLS.2024.3361087","article-title":"A novel generator with auxiliary branch for improving GAN performance","volume":"36","author":"Park","year":"2025","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"10.1016\/j.neucom.2026.134412_bib0080","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","article-title":"Squeeze-and-excitation networks","author":"Hu","year":"2018"},{"key":"10.1016\/j.neucom.2026.134412_bib0085","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","article-title":"ECA-net: efficient channel attention for deep convolutional neural networks","author":"Wang","year":"2020"},{"key":"10.1016\/j.neucom.2026.134412_bib0090","series-title":"Proceedings of the European Conference on Computer Vision (ECCV)","article-title":"CBAM: convolutional block attention module","author":"Woo","year":"2018"},{"key":"10.1016\/j.neucom.2026.134412_bib0095","series-title":"Advances in Neural Information Processing Systems, 30","article-title":"Attention is all you need","author":"Vaswani","year":"2017"},{"key":"10.1016\/j.neucom.2026.134412_bib0100","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","article-title":"Mimicking very efficient network for object detection","author":"Li","year":"2017"},{"key":"10.1016\/j.neucom.2026.134412_bib0105","series-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV)","first-page":"5311","article-title":"Channel-wise knowledge distillation for dense prediction","author":"Shu","year":"2021"},{"key":"10.1016\/j.neucom.2026.134412_bib0110","series-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV)","article-title":"Be your own teacher: improve the performance of convolutional neural networks via self distillation","author":"Zhang","year":"2019"},{"key":"10.1016\/j.neucom.2026.134412_bib0115","doi-asserted-by":"crossref","first-page":"6165","DOI":"10.1007\/s11063-022-11132-w","article-title":"Knowledge fusion distillation: improving distillation with multi-scale attention mechanisms","volume":"55","author":"Li","year":"2023","journal-title":"Neural Process. Lett."},{"key":"10.1016\/j.neucom.2026.134412_bib0120","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"10664","article-title":"Refine myself by teaching myself: feature refinement via self-knowledge distillation","author":"Ji","year":"2021"},{"key":"10.1016\/j.neucom.2026.134412_bib0125","article-title":"A lightweight network enhanced by attention-guided cross-scale interaction for underwater object detection","author":"Zhang","year":"2025","journal-title":"Appl. Soft Comput."},{"key":"10.1016\/j.neucom.2026.134412_bib0130","article-title":"An innovative neural network architecture designed for industrial fault diagnosis with hierarchical adaptive attention mechanism","author":"Wu","year":"2025","journal-title":"Process Saf. Environ. Prot."},{"key":"10.1016\/j.neucom.2026.134412_bib0135","doi-asserted-by":"crossref","first-page":"9528","DOI":"10.1109\/TNNLS.2022.3151138","article-title":"DualConv: dual convolutional kernels for lightweight deep neural networks","volume":"34","author":"Zhong","year":"2023","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"10.1016\/j.neucom.2026.134412_bib0140","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"13733","article-title":"RepVGG: making VGG-style ConvNets great again","author":"Ding","year":"2021"},{"key":"10.1016\/j.neucom.2026.134412_bib0145","doi-asserted-by":"crossref","DOI":"10.1109\/TSMC.2026.3661716","article-title":"Dynamic event-triggered control for human-machine cooperative systems based on dynamic authority allocation","author":"Zhang","year":"2026","journal-title":"IEEE Trans. Syst. Man Cybern. Syst."},{"key":"10.1016\/j.neucom.2026.134412_bib0150","article-title":"Dynamic event-triggered approximate optimal consensus control for unknown nonlinear multi-agent systems via adaptive dynamic programming","author":"Zhang","year":"2026","journal-title":"ISA Trans."},{"key":"10.1016\/j.neucom.2026.134412_bib0155","doi-asserted-by":"crossref","first-page":"1904","DOI":"10.1109\/TPAMI.2015.2389824","article-title":"Spatial pyramid pooling in deep convolutional networks for visual recognition","volume":"37","author":"He","year":"2015","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.neucom.2026.134412_bib0160","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2025.129866","article-title":"SCSA: exploring the synergistic effects between spatial and channel attention","volume":"634","author":"Si","year":"2025","journal-title":"Neurocomputing"},{"key":"10.1016\/j.neucom.2026.134412_bib0165","doi-asserted-by":"crossref","first-page":"1527","DOI":"10.1162\/neco.2006.18.7.1527","article-title":"A fast learning algorithm for deep belief nets","volume":"18","author":"Hinton","year":"2006","journal-title":"Neural Comput."},{"key":"10.1016\/j.neucom.2026.134412_bib0170","series-title":"Proceedings of the AAAI Conference on Artificial Intelligence, 34","first-page":"12993","article-title":"Distance-IoU loss: faster and better learning for bounding box regression","author":"Zheng","year":"2020"},{"key":"10.1016\/j.neucom.2026.134412_bib0175","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"5513","article-title":"UniRepLKNet: a universal perception large-kernel ConvNet for audio video point cloud time-series and image recognition","author":"Ding","year":"2024"},{"key":"10.1016\/j.neucom.2026.134412_bib0180","series-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV)","first-page":"10012","article-title":"Swin transformer: hierarchical vision transformer using shifted windows","author":"Liu","year":"2021"},{"key":"10.1016\/j.neucom.2026.134412_bib0185","series-title":"Advances in Neural Information Processing Systems, 36","first-page":"7050","article-title":"VanillaNet: the power of minimalism in deep learning","author":"Chen","year":"2023"},{"key":"10.1016\/j.neucom.2026.134412_bib0190","author":"Howard"},{"key":"10.1016\/j.neucom.2026.134412_bib0195","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","article-title":"MobileNetV2: inverted residuals and linear bottlenecks","author":"Sandler","year":"2018"},{"key":"10.1016\/j.neucom.2026.134412_bib0200","series-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV)","article-title":"Searching for MobileNetV3","author":"Howard","year":"2019"},{"key":"10.1016\/j.neucom.2026.134412_bib0205","series-title":"Computer Vision \u2013 ECCV 2024","first-page":"78","article-title":"MobileNetV4: universal models for the mobile ecosystem","author":"Qin","year":"2025"},{"key":"10.1016\/j.neucom.2026.134412_bib0210","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"15909","article-title":"RepViT: revisiting mobile CNN from ViT perspective","author":"Wang","year":"2024"},{"key":"10.1016\/j.neucom.2026.134412_bib0215","author":"Mehta"},{"key":"10.1016\/j.neucom.2026.134412_bib0220","author":"Mehta"},{"key":"10.1016\/j.neucom.2026.134412_bib0225","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"12021","article-title":"Run, don\u2019t walk: chasing higher FLOPS for faster neural networks","author":"Chen","year":"2023"},{"key":"10.1016\/j.neucom.2026.134412_bib0230","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"16133","article-title":"ConvNeXt v2: co-designing and scaling ConvNets with masked autoencoders","author":"Woo","year":"2023"},{"key":"10.1016\/j.neucom.2026.134412_bib0235","series-title":"Advances in Neural Information Processing Systems, 35","first-page":"9969","article-title":"GhostNetV2: enhance cheap operation with long-range attention","author":"Tang","year":"2022"},{"key":"10.1016\/j.neucom.2026.134412_bib0240","series-title":"Proceedings of the 38th International Conference on Machine Learning, 139","first-page":"10096","article-title":"EfficientNetV2: smaller models and faster training","author":"Tan","year":"2021"},{"key":"10.1016\/j.neucom.2026.134412_bib0245","series-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV)","first-page":"16794","article-title":"Large selective kernel network for remote sensing object detection","author":"Li","year":"2023"},{"key":"10.1016\/j.neucom.2026.134412_bib0250","series-title":"2023 IEEE\/CVF International Conference on Computer Vision (ICCV)","first-page":"1389","article-title":"Rethinking mobile block for efficient attention-based models","author":"Zhang","year":"2023"},{"key":"10.1016\/j.neucom.2026.134412_bib0255","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"5672","article-title":"InceptionNeXt: when inception meets ConvNeXt","author":"Yu","year":"2024"},{"key":"10.1016\/j.neucom.2026.134412_bib0260","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"4484","article-title":"MambaOut: do we really need Mamba for vision?","author":"Yu","year":"2025"},{"key":"10.1016\/j.neucom.2026.134412_bib0265","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"10819","article-title":"MetaFormer is actually what you need for vision","author":"Yu","year":"2022"},{"key":"10.1016\/j.neucom.2026.134412_bib0270","author":"Zhou"},{"key":"10.1016\/j.neucom.2026.134412_bib0275","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","article-title":"EfficientDet: scalable and efficient object detection","author":"Tan","year":"2020"},{"key":"10.1016\/j.neucom.2026.134412_bib0280","series-title":"Computer Vision \u2013 ECCV 2016","first-page":"21","article-title":"SSD: single shot MultiBox detector","author":"Liu","year":"2016"},{"key":"10.1016\/j.neucom.2026.134412_bib0285","series-title":"Advances in Neural Information Processing Systems, 28","article-title":"Faster R-CNN: towards real-time object detection with region proposal networks","author":"Ren","year":"2015"},{"key":"10.1016\/j.neucom.2026.134412_bib0290","author":"Khanam"},{"key":"10.1016\/j.neucom.2026.134412_bib0295","author":"Li"},{"key":"10.1016\/j.neucom.2026.134412_bib0300","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"7464","article-title":"YOLOv7: trainable bag-of-freebies sets new state-of-the-art for real-time object detectors","author":"Wang","year":"2023"},{"key":"10.1016\/j.neucom.2026.134412_bib0305","series-title":"2024 International Conference on Advances in Data Engineering and Intelligent Computing Systems (ADICS)","first-page":"1","article-title":"YOLOv8: a novel object detection algorithm with enhanced performance and robustness","author":"Varghese","year":"2024"},{"key":"10.1016\/j.neucom.2026.134412_bib0310","author":"Ge"},{"key":"10.1016\/j.neucom.2026.134412_bib0315","series-title":"Advances in Neural Information Processing Systems, 37","first-page":"107984","article-title":"YOLOv10: real-time end-to-end object detection","author":"Wang","year":"2024"},{"key":"10.1016\/j.neucom.2026.134412_bib0320","author":"Khanam"},{"key":"10.1016\/j.neucom.2026.134412_bib0325","author":"Tian"},{"key":"10.1016\/j.neucom.2026.134412_bib0330","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"16965","article-title":"DETRs beat YOLOs on real-time object detection","author":"Zhao","year":"2024"},{"key":"10.1016\/j.neucom.2026.134412_bib0335","series-title":"Computer Vision \u2013 ECCV 2020","first-page":"213","article-title":"End-to-end object detection with transformers","author":"Carion","year":"2020"},{"key":"10.1016\/j.neucom.2026.134412_bib0340","doi-asserted-by":"crossref","first-page":"1562","DOI":"10.3390\/s20061562","article-title":"Deep metallic surface defect detection: the new benchmark and detection network","volume":"20","author":"Lv","year":"2020","journal-title":"Sensors"}],"container-title":["Neurocomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0925231226018102?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0925231226018102?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T11:10:29Z","timestamp":1783595429000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0925231226018102"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10]]},"references-count":68,"alternative-id":["S0925231226018102"],"URL":"https:\/\/doi.org\/10.1016\/j.neucom.2026.134412","relation":{},"ISSN":["0925-2312"],"issn-type":[{"value":"0925-2312","type":"print"}],"subject":[],"published":{"date-parts":[[2026,10]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"SHMNet: A lightweight backbone network with an auxiliary branch for blister pharmaceutical detection","name":"articletitle","label":"Article Title"},{"value":"Neurocomputing","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.neucom.2026.134412","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"134412"}}