{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T10:13:11Z","timestamp":1767262391173,"version":"3.46.0"},"reference-count":51,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"3","license":[{"start":{"date-parts":[[2025,3,1]],"date-time":"2025-03-01T00:00:00Z","timestamp":1740787200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,3,1]],"date-time":"2025-03-01T00:00:00Z","timestamp":1740787200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,3,1]],"date-time":"2025-03-01T00:00:00Z","timestamp":1740787200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62141602","61976120"],"award-info":[{"award-number":["62141602","61976120"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003392","name":"Natural Science Foundation of Fujian Province","doi-asserted-by":"publisher","award":["2021J011003","2021J02049"],"award-info":[{"award-number":["2021J011003","2021J02049"]}],"id":[{"id":"10.13039\/501100003392","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004608","name":"Natural Science Foundation of Jiangsu Province","doi-asserted-by":"publisher","award":["BK20231337"],"award-info":[{"award-number":["BK20231337"]}],"id":[{"id":"10.13039\/501100004608","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Natural Science Key Foundation of Jiangsu Education Department","award":["21KJA510004"],"award-info":[{"award-number":["21KJA510004"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Neural Netw. Learning Syst."],"published-print":{"date-parts":[[2025,3]]},"DOI":"10.1109\/tnnls.2024.3380833","type":"journal-article","created":{"date-parts":[[2024,4,1]],"date-time":"2024-04-01T16:01:58Z","timestamp":1711987318000},"page":"5721-5733","source":"Crossref","is-referenced-by-count":5,"title":["CSTS: Exploring Class-Specific and Task-Shared Embedding Representation for Few-Shot Learning"],"prefix":"10.1109","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9339-1829","authenticated-orcid":false,"given":"Hong","family":"Zhao","sequence":"first","affiliation":[{"name":"School of Computer Science, Minnan Normal University, Zhangzhou, Fujian, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-1758-9750","authenticated-orcid":false,"given":"Yuling","family":"Su","sequence":"additional","affiliation":[{"name":"School of Computer Science, Minnan Normal University, Zhangzhou, Fujian, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3578-9024","authenticated-orcid":false,"given":"Zhiping","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Computer Science, Minnan Normal University, Zhangzhou, Fujian, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3180-7347","authenticated-orcid":false,"given":"Weiping","family":"Ding","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, Nantong University, Nantong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00870"},{"key":"ref2","first-page":"3637","article-title":"Matching networks for one shot learning","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Vinyals"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2023.3261387"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00874"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR48806.2021.9412926"},{"key":"ref6","first-page":"1126","article-title":"Model-agnostic meta-learning for fast adaptation of deep networks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Finn"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00049"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00131"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01222"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2022.109024"},{"key":"ref11","first-page":"1","article-title":"Learning to propagate labels: Transductive propagation network for few-shot learning","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Liu"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00620"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/3394171.3413811"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01340"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i07.6630"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2021.3058098"},{"key":"ref17","first-page":"18661","article-title":"Supervised contrastive learning","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"33","author":"Khosla"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijar.2021.12.013"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01091"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58604-1_25"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ICMEW.2019.00041"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.5555\/3294996.3295163"},{"key":"ref23","first-page":"1","article-title":"Few-shot learning with graph neural networks","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Garcia"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.2978386"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00010"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00738"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-020-01342-x"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00653"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58621-8_45"},{"key":"ref30","first-page":"140","article-title":"Contrastive prototype learning with augmented embeddings for few-shot learning","volume-title":"Proc. 37th Conf. Uncertainty Artif. Intell.","author":"Gao"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-86486-6_41"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i10.17047"},{"key":"ref33","article-title":"Dual prototypical contrastive learning for few-shot semantic segmentation","author":"Kwon","year":"2021","journal-title":"arXiv:2111.04982"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2019.2960251"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2021.3100928"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1145\/219717.219748"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00975"},{"key":"ref38","first-page":"1","article-title":"Meta-learning for semi-supervised few-shot classification","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Ren"},{"key":"ref39","first-page":"1","article-title":"Meta-learning with differentiable closed-form solvers","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Bertinetto"},{"article-title":"The Caltech-UCSD birds-200\u20132011 dataset","year":"2011","author":"Wah","key":"ref40"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00883"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58574-7_8"},{"key":"ref43","first-page":"13230","article-title":"Learning to learn dense Gaussian processes for few-shot learning","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"34","author":"Wang"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/WACV56688.2023.00250"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3107164"},{"key":"ref46","first-page":"9122","article-title":"Learning to learn variational semantic memory","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"33","author":"Zhen"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00256"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-20044-1_26"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00069"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2020.3004555"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00893"}],"container-title":["IEEE Transactions on Neural Networks and Learning Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/5962385\/10908444\/10486859.pdf?arnumber=10486859","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,5]],"date-time":"2025-12-05T18:39:08Z","timestamp":1764959948000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10486859\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,3]]},"references-count":51,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.1109\/tnnls.2024.3380833","relation":{},"ISSN":["2162-237X","2162-2388"],"issn-type":[{"type":"print","value":"2162-237X"},{"type":"electronic","value":"2162-2388"}],"subject":[],"published":{"date-parts":[[2025,3]]}}}