{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,8]],"date-time":"2026-06-08T20:57:56Z","timestamp":1780952276782,"version":"3.54.1"},"reference-count":50,"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":["Information Sciences"],"published-print":{"date-parts":[[2026,10]]},"DOI":"10.1016\/j.ins.2026.123744","type":"journal-article","created":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T16:19:12Z","timestamp":1780589952000},"page":"123744","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Explicit location-label-guided foreground feature optimization learning for few-shot classification"],"prefix":"10.1016","volume":"754","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4561-6445","authenticated-orcid":false,"given":"Bin","family":"Song","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2993-1928","authenticated-orcid":false,"given":"Hong","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-3508-2942","authenticated-orcid":false,"given":"Bingxin","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7087-131X","authenticated-orcid":false,"given":"Yuandong","family":"Bi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.ins.2026.123744_bib0005","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"7972","article-title":"Joint distribution matters: deep brownian distance covariance for few-shot classification","author":"Xie","year":"2022"},{"key":"10.1016\/j.ins.2026.123744_bib0010","first-page":"3582","article-title":"Rethinking generalization in few-shot classification","volume":"35","author":"Hiller","year":"2022","journal-title":"Adv. Neural Inf. Process. Syst."},{"issue":"8","key":"10.1016\/j.ins.2026.123744_bib0015","doi-asserted-by":"crossref","first-page":"3947","DOI":"10.1109\/TCSVT.2023.3236636","article-title":"Boosting few-shot fine-grained recognition with background suppression and foreground alignment","volume":"33","author":"Zha","year":"2023","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.ins.2026.123744_bib0020","series-title":"European Conference on Computer Vision","first-page":"38","article-title":"Grounding DINO: marrying DINO with grounded pre-training for open-set object detection","author":"Liu","year":"2025"},{"key":"10.1016\/j.ins.2026.123744_bib0025","series-title":"International Conference on Machine Learning","first-page":"1126","article-title":"Model-agnostic meta-learning for fast adaptation of deep networks","author":"Finn","year":"2017"},{"issue":"3","key":"10.1016\/j.ins.2026.123744_bib0030","doi-asserted-by":"crossref","first-page":"1425","DOI":"10.1109\/TPAMI.2022.3160362","article-title":"Few-shot learning with a strong teacher","volume":"46","author":"Ye","year":"2024","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.ins.2026.123744_bib0035","article-title":"Prototypical networks for few-shot learning","volume":"30","author":"Snell","year":"2017","journal-title":"Adv. Neural Inf. Process. Syst."},{"issue":"8","key":"10.1016\/j.ins.2026.123744_bib0040","doi-asserted-by":"crossref","first-page":"6592","DOI":"10.1007\/s10489-024-05516-9","article-title":"A conditioned feature reconstruction network for few-shot classification","volume":"54","author":"Song","year":"2024","journal-title":"Appl. Intell."},{"key":"10.1016\/j.ins.2026.123744_bib0045","series-title":"International Conference on Learning Representations","article-title":"A closer look at few-shot classification","author":"Chen","year":"2019"},{"key":"10.1016\/j.ins.2026.123744_bib0050","series-title":"Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision","first-page":"2218","article-title":"Charting the right manifold: manifold mixup for few-shot learning","author":"Mangla","year":"2020"},{"key":"10.1016\/j.ins.2026.123744_bib0055","series-title":"Computer Vision\u2013ECCV 2020: 16th European Conference, Glasgow, UK, August 23\u201328, 2020, Proceedings, Part XIV 16","first-page":"266","article-title":"Rethinking few-shot image classification: a good embedding is all you need?","author":"Tian","year":"2020"},{"key":"10.1016\/j.ins.2026.123744_bib0060","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"9068","article-title":"Pushing the limits of simple pipelines for few-shot learning: external data and fine-tuning make a difference","author":"Hu","year":"2022"},{"key":"10.1016\/j.ins.2026.123744_bib0065","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"9003","article-title":"Generating representative samples for few-shot classification","author":"Xu","year":"2022"},{"issue":"1","key":"10.1016\/j.ins.2026.123744_bib0070","doi-asserted-by":"crossref","DOI":"10.1049\/cvi2.70051","article-title":"Prior matters: contribution-and semantics-aware prior estimation for few-shot learning","volume":"19","author":"Tian","year":"2025","journal-title":"IET Comput. Vis."},{"key":"10.1016\/j.ins.2026.123744_bib0075","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2024.125905","article-title":"Orthogonal progressive network for few-shot object detection","volume":"264","author":"Wang","year":"2025","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.ins.2026.123744_bib0080","series-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","first-page":"8420","article-title":"Few-shot object detection via feature reweighting","author":"Kang","year":"2019"},{"key":"10.1016\/j.ins.2026.123744_bib0085","series-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","first-page":"9577","article-title":"Meta R-CNN: towards general solver for instance-level low-shot learning","author":"Yan","year":"2019"},{"key":"10.1016\/j.ins.2026.123744_bib0090","series-title":"Proceedings of the AAAI Conference on Artificial Intelligence, 37","first-page":"755","article-title":"Few-shot object detection via variational feature aggregation","author":"Han","year":"2023"},{"key":"10.1016\/j.ins.2026.123744_bib0095","series-title":"International Conference on Machine Learning","first-page":"9919","article-title":"Frustratingly simple few-shot object detection","author":"Wang","year":"2020"},{"key":"10.1016\/j.ins.2026.123744_bib0100","series-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","first-page":"8681","article-title":"Defrcn: decoupled faster R-CNN for few-shot object detection","author":"Qiao","year":"2021"},{"key":"10.1016\/j.ins.2026.123744_bib0105","first-page":"51955","article-title":"Promises and pitfalls of threshold-based auto-labeling","volume":"36","author":"Vishwakarma","year":"2024","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.ins.2026.123744_bib0110","series-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","first-page":"4015","article-title":"Segment anything","author":"Kirillov","year":"2023"},{"key":"10.1016\/j.ins.2026.123744_bib0115","series-title":"International Conference on Machine Learning, 139","first-page":"8748","article-title":"Learning transferable visual models from natural language supervision","author":"Radford","year":"2021"},{"key":"10.1016\/j.ins.2026.123744_bib0120","author":"Huang"},{"key":"10.1016\/j.ins.2026.123744_bib0125","series-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","first-page":"4918","article-title":"Rethinking imagenet pre-training","author":"He","year":"2019"},{"key":"10.1016\/j.ins.2026.123744_bib0130","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"8012","article-title":"Few-shot classification with feature map reconstruction networks","author":"Wertheimer","year":"2021"},{"issue":"5","key":"10.1016\/j.ins.2026.123744_bib0135","first-page":"5632","article-title":"Deepemd: differentiable earth mover\u2019s distance for few-shot learning","volume":"45","author":"Zhang","year":"2022","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.ins.2026.123744_bib0140","series-title":"European Conference on Computer Vision","first-page":"740","article-title":"Self-supervision can be a good few-shot learner","author":"Lu","year":"2022"},{"issue":"18","key":"10.1016\/j.ins.2026.123744_bib0145","doi-asserted-by":"crossref","first-page":"20661","DOI":"10.1007\/s10489-023-04525-4","article-title":"Self-supervised pairwise-sample resistance model for few-shot classification","volume":"53","author":"Li","year":"2023","journal-title":"Appl. Intell."},{"key":"10.1016\/j.ins.2026.123744_bib0150","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2023.110798","article-title":"Detach and unite: a simple meta-transfer for few-shot learning","volume":"277","author":"Zheng","year":"2023","journal-title":"Knowl.-based Syst."},{"key":"10.1016\/j.ins.2026.123744_bib0155","series-title":"Proceedings of the AAAI Conference on Artificial Intelligence, 37","first-page":"9596","article-title":"ESPT: a self-supervised episodic spatial pretext task for improving few-shot learning","author":"Rong","year":"2023"},{"key":"10.1016\/j.ins.2026.123744_bib0160","article-title":"Disentangled feature representation for few-shot image classification","author":"Cheng","year":"2023","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"issue":"3","key":"10.1016\/j.ins.2026.123744_bib0165","doi-asserted-by":"crossref","first-page":"1441","DOI":"10.1109\/TPAMI.2023.3261387","article-title":"Learning to learn task-adaptive hyperparameters for few-shot learning","volume":"46","author":"Baik","year":"2023","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"4","key":"10.1016\/j.ins.2026.123744_bib0170","doi-asserted-by":"crossref","first-page":"10865","DOI":"10.1007\/s11042-023-15892-y","article-title":"MCS: a metric confidence selection framework for few shot image classification","volume":"83","author":"Wang","year":"2024","journal-title":"Multimed. Tools Appl."},{"issue":"8","key":"10.1016\/j.ins.2026.123744_bib0175","doi-asserted-by":"crossref","first-page":"10751","DOI":"10.1109\/TNNLS.2023.3243903","article-title":"Task-related saliency for few-shot image classification","volume":"35","author":"Zhou","year":"2024","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"10.1016\/j.ins.2026.123744_bib0180","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2024.110805","article-title":"Few-shot classification with fork attention adapter","volume":"156","author":"Sun","year":"2024","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.ins.2026.123744_bib0185","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1016\/j.patrec.2022.06.012","article-title":"Baby steps towards few-shot learning with multiple semantics","volume":"160","author":"Schwartz","year":"2022","journal-title":"Pattern Recognit. Lett."},{"key":"10.1016\/j.ins.2026.123744_bib0190","series-title":"Proceedings of the 29th ACM International Conference on Multimedia","first-page":"107","article-title":"Object-aware long-short-range spatial alignment for few-shot fine-grained image classification","author":"Wu","year":"2021"},{"key":"10.1016\/j.ins.2026.123744_bib0195","series-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","first-page":"8812","article-title":"Variational feature disentangling for fine-grained few-shot classification","author":"Xu","year":"2021"},{"key":"10.1016\/j.ins.2026.123744_bib0200","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2022.108792","article-title":"Learning attention-guided pyramidal features for few-shot fine-grained recognition","volume":"130","author":"Tang","year":"2022","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.ins.2026.123744_bib0205","doi-asserted-by":"crossref","first-page":"7529","DOI":"10.1109\/TMM.2024.3369870","article-title":"Robust saliency-aware distillation for few-shot fine-grained visual recognition","volume":"26","author":"Liu","year":"2024","journal-title":"IEEE Trans. Multimed."},{"issue":"7","key":"10.1016\/j.ins.2026.123744_bib0210","doi-asserted-by":"crossref","first-page":"4351","DOI":"10.1109\/TCSVT.2021.3132912","article-title":"Global-local interplay in semantic alignment for few-shot learning","volume":"32","author":"Hao","year":"2021","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"issue":"9","key":"10.1016\/j.ins.2026.123744_bib0215","doi-asserted-by":"crossref","first-page":"6240","DOI":"10.1109\/TCSVT.2022.3165068","article-title":"Task encoding with distribution calibration for few-shot learning","volume":"32","author":"Zhang","year":"2022","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.ins.2026.123744_bib0220","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2024.110485","article-title":"Self-reconstruction network for fine-grained few-shot classification","volume":"153","author":"Li","year":"2024","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.ins.2026.123744_bib0225","doi-asserted-by":"crossref","first-page":"1318","DOI":"10.1109\/TIP.2020.3043128","article-title":"BSNet: bi-similarity network for few-shot fine-grained image classification","volume":"30","author":"Li","year":"2020","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.ins.2026.123744_bib0230","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2024.128448","article-title":"Few-shot image classification using graph neural network with fine-grained feature descriptors","volume":"610","author":"Ganesan","year":"2024","journal-title":"Neurocomputing"},{"key":"10.1016\/j.ins.2026.123744_bib0235","first-page":"113697","article-title":"VT-fsl: bridging vision and text with LLMs for few-shot learning","volume":"38","author":"Li","year":"2026","journal-title":"Adv. Neural Inf. Process. Syst."},{"issue":"12","key":"10.1016\/j.ins.2026.123744_bib0240","doi-asserted-by":"crossref","first-page":"7530","DOI":"10.1109\/TCSVT.2023.3275382","article-title":"Locally-enriched cross-reconstruction for few-shot fine-grained image classification","volume":"33","author":"Li","year":"2023","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.ins.2026.123744_bib0245","first-page":"1","article-title":"Improved fine-grained image classification in few-shot learning based on channel-spatial attention and grouped bilinear convolution","author":"Zeng","year":"2024","journal-title":"Vis. Comput."},{"issue":"9","key":"10.1016\/j.ins.2026.123744_bib0250","doi-asserted-by":"crossref","first-page":"6082","DOI":"10.1109\/TPAMI.2024.3376686","article-title":"Bi-directional ensemble feature reconstruction network for few-shot fine-grained classification","volume":"46","author":"Wu","year":"2024","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."}],"container-title":["Information Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0020025526006754?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0020025526006754?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,6,8]],"date-time":"2026-06-08T20:07:06Z","timestamp":1780949226000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0020025526006754"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10]]},"references-count":50,"alternative-id":["S0020025526006754"],"URL":"https:\/\/doi.org\/10.1016\/j.ins.2026.123744","relation":{},"ISSN":["0020-0255"],"issn-type":[{"value":"0020-0255","type":"print"}],"subject":[],"published":{"date-parts":[[2026,10]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Explicit location-label-guided foreground feature optimization learning for few-shot classification","name":"articletitle","label":"Article Title"},{"value":"Information Sciences","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.ins.2026.123744","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"123744"}}