{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T19:23:05Z","timestamp":1757618585940,"version":"3.44.0"},"reference-count":23,"publisher":"Springer Science and Business Media LLC","issue":"10","license":[{"start":{"date-parts":[[2025,7,9]],"date-time":"2025-07-09T00:00:00Z","timestamp":1752019200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,7,9]],"date-time":"2025-07-09T00:00:00Z","timestamp":1752019200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"Youth Fund of Shanghai Second Polytechnic University","award":["EGD25QD02"],"award-info":[{"award-number":["EGD25QD02"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Supercomput"],"DOI":"10.1007\/s11227-025-07553-8","type":"journal-article","created":{"date-parts":[[2025,7,10]],"date-time":"2025-07-10T09:32:34Z","timestamp":1752139954000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A single multi-task deep neural network with a multi-scale feature aggregation mechanism for manipulation relationship reasoning in robotic grasping"],"prefix":"10.1007","volume":"81","author":[{"given":"Mingshuai","family":"Dong","sequence":"first","affiliation":[]},{"given":"Yuxuan","family":"Bai","sequence":"additional","affiliation":[]},{"given":"Xiuli","family":"Yu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,7,9]]},"reference":[{"doi-asserted-by":"crossref","unstructured":"Guo D, Sun F, Liu H, Kong T, Fang B, Xi N (2017) A hybrid deep architecture for robotic grasp detection. In: 2017 IEEE International Conference on Robotics and Automation (ICRA)","key":"7553_CR1","DOI":"10.1109\/ICRA.2017.7989191"},{"doi-asserted-by":"crossref","unstructured":"Zhou X, Lan X, Zhang H, Tian Z, Zhang Y, Zheng N (2018) Fully convolutional grasp detection network with oriented anchor box. IEEE","key":"7553_CR2","DOI":"10.1109\/IROS.2018.8594116"},{"key":"7553_CR3","doi-asserted-by":"publisher","first-page":"3355","DOI":"10.1109\/LRA.2018.2852777","volume":"3","author":"FJ Chu","year":"2018","unstructured":"Chu FJ, Xu R, Patricio V (2018) Real-world multiobject, multigrasp detection. IEEE Robot Autom Lett 3:3355\u20133362","journal-title":"IEEE Robot Autom Lett"},{"doi-asserted-by":"crossref","unstructured":"Redmon J, Angelova A (2015) Real-time grasp detection using convolutional neural networks. In: 2015 IEEE International Conference on Robotics and Automation (ICRA), pp. 1316\u20131322 . IEEE","key":"7553_CR4","DOI":"10.1109\/ICRA.2015.7139361"},{"key":"7553_CR5","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1016\/j.patrec.2020.09.014","volume":"140","author":"H Zhang","year":"2020","unstructured":"Zhang H, Lan X, Zhou X, Tian Z, Zheng N (2020) Visual manipulation relationship recognition in object-stacking scenes. Pattern Recognit Lett 140:34\u201342","journal-title":"Pattern Recognit Lett"},{"doi-asserted-by":"crossref","unstructured":"Park D, Seo Y, Shin D, Choi J, Chun SY (2019) A single multi-task deep neural network with post-processing for object detection with reasoning and robotic grasp detection","key":"7553_CR6","DOI":"10.1109\/ICRA40945.2020.9197179"},{"key":"7553_CR7","doi-asserted-by":"publisher","DOI":"10.3389\/fnbot.2021.719731","author":"G Zuo","year":"2021","unstructured":"Zuo G, Tong J, Liu H, Chen W, Li J (2021) Graph-based visual manipulation relationship reasoning network for robotic grasping. Front Neurorobotics. https:\/\/doi.org\/10.3389\/fnbot.2021.719731","journal-title":"Front Neurorobotics"},{"doi-asserted-by":"crossref","unstructured":"Wang H, Zhang Y, Wang Y, Li J (2024) 6-dof grasp detection in clutter with enhanced receptive field and graspable balance sampling. In: 2024 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 3000\u20133007. IEEE","key":"7553_CR8","DOI":"10.1109\/IROS58592.2024.10802025"},{"doi-asserted-by":"crossref","unstructured":"Li Y, Kong T, Chu R, Li Y, Wang P, Li L (2021) Simultaneous semantic and collision learning for 6-dof grasp pose estimation. in 2021 ieee. In: RSJ International Conference on Intelligent Robots and Systems (IROS), vol. 27","key":"7553_CR9","DOI":"10.1109\/IROS51168.2021.9636012"},{"doi-asserted-by":"crossref","unstructured":"Chen Y, Lin Y, Xu R, Vela PA (2023) Keypoint-graspnet: Keypoint-based 6-dof grasp generation from the monocular rgb-d input. In: 2023 IEEE International Conference on Robotics and Automation (ICRA), pp. 7988\u20137995. IEEE","key":"7553_CR10","DOI":"10.1109\/ICRA48891.2023.10161284"},{"key":"7553_CR11","doi-asserted-by":"publisher","DOI":"10.1016\/j.rcim.2020.101963","volume":"65","author":"Y Song","year":"2020","unstructured":"Song Y, Gao L, Li X, Shen W (2020) A novel robotic grasp detection method based on region proposal networks. Robot Comput Integr Manuf 65:101963","journal-title":"Robot Comput Integr Manuf"},{"issue":"2","key":"7553_CR12","doi-asserted-by":"publisher","first-page":"1167","DOI":"10.1109\/TSMC.2020.3018757","volume":"52","author":"Y Yu","year":"2022","unstructured":"Yu Y, Cao Z, Liu Z, Geng W, Yu J, Zhang W (2022) A two-stream cnn with simultaneous detection and segmentation for robotic grasping. IEEE Trans Syst Man and Cybern Syst 52(2):1167\u20131181","journal-title":"IEEE Trans Syst Man and Cybern Syst"},{"key":"7553_CR13","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s11063-023-11318-w","volume":"55","author":"M Dong","year":"2023","unstructured":"Dong M, Bai Y, Wei S, Yu X (2023) Real-world semantic grasp detection using ontology features: learning to concentrate on object features. Neural Proc Lett 55:1\u201321","journal-title":"Neural Proc Lett"},{"doi-asserted-by":"crossref","unstructured":"Wang S, Zhou Z, Kan Z (2022) When transformer meets robotic grasping: Exploits context for efficient grasp detection. arXiv e-prints","key":"7553_CR14","DOI":"10.1109\/LRA.2022.3187261"},{"doi-asserted-by":"crossref","unstructured":"Dong M, Bai Y, Wei S, Yu X (2022) Robotic grasp detection based on transformer, vol 13458. LNAI. Harbin, China, pp 437\u2013448","key":"7553_CR15","DOI":"10.1007\/978-3-031-13841-6_40"},{"doi-asserted-by":"crossref","unstructured":"Tripathi A, Srivastava S, Lall B, Chaudhury S (2021) Using scene graphs for detecting visual relationships. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 10074\u201310081. IEEE","key":"7553_CR16","DOI":"10.1109\/ICPR48806.2021.9412337"},{"doi-asserted-by":"crossref","unstructured":"Dai B, Zhang Y, Lin D (2017) Detecting visual relationships with deep relational networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3076\u20133086","key":"7553_CR17","DOI":"10.1109\/CVPR.2017.352"},{"doi-asserted-by":"crossref","unstructured":"Liang X, Lee L, Xing EP (2017) Deep variation-structured reinforcement learning for visual relationship and attribute detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 848\u2013857","key":"7553_CR18","DOI":"10.1109\/CVPR.2017.469"},{"key":"7553_CR19","first-page":"5","volume":"34","author":"I Lenz","year":"2013","unstructured":"Lenz I, Lee H, Saxena A (2013) Deep learning for detecting robotic grasps. Int J Robot Res 34:5","journal-title":"Int J Robot Res"},{"key":"7553_CR20","first-page":"3014","volume":"5","author":"H Zhang","year":"2018","unstructured":"Zhang H, Zhou X, Lan X, Jin L, Zheng N (2018) A real-time robotic grasp approach with oriented anchor box. IEEE Trans Syst Man Cybernet Syst 5:3014","journal-title":"IEEE Trans Syst Man Cybernet Syst"},{"issue":"6","key":"7553_CR21","doi-asserted-by":"publisher","first-page":"1137","DOI":"10.1109\/TPAMI.2016.2577031","volume":"39","author":"S Ren","year":"2017","unstructured":"Ren S, He K, Girshick R, Sun J (2017) Faster r-cnn: towards real-time object detection with region proposal networks. IEEE Trans Pattern Anal Mach Intell 39(6):1137\u20131149","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"doi-asserted-by":"crossref","unstructured":"Zhang H, Lan X, Bai S, Wan L, Yang C, Zheng N (2019) A multi-task convolutional neural network for autonomous robotic grasping in object stacking scenes. In: 2019 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 6435\u20136442. IEEE","key":"7553_CR22","DOI":"10.1109\/IROS40897.2019.8967977"},{"doi-asserted-by":"crossref","unstructured":"Zhang H, Lan X, Zhou X, Tian Z, Zheng N (2018) Visual manipulation relationship network for autonomous robotics. In: 2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids)","key":"7553_CR23","DOI":"10.1109\/HUMANOIDS.2018.8625071"}],"container-title":["The Journal of Supercomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-025-07553-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11227-025-07553-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-025-07553-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,7]],"date-time":"2025-09-07T01:45:21Z","timestamp":1757209521000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11227-025-07553-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,9]]},"references-count":23,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2025,7]]}},"alternative-id":["7553"],"URL":"https:\/\/doi.org\/10.1007\/s11227-025-07553-8","relation":{},"ISSN":["1573-0484"],"issn-type":[{"type":"electronic","value":"1573-0484"}],"subject":[],"published":{"date-parts":[[2025,7,9]]},"assertion":[{"value":"2 June 2025","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 July 2025","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors have no relevant financial or non-financial interests to disclose.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"1126"}}