{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T03:51:55Z","timestamp":1776138715498,"version":"3.50.1"},"reference-count":36,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T00:00:00Z","timestamp":1773705600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52304036"],"award-info":[{"award-number":["52304036"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Engineering Applications of Artificial Intelligence"],"published-print":{"date-parts":[[2026,6]]},"DOI":"10.1016\/j.engappai.2026.114542","type":"journal-article","created":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T08:34:18Z","timestamp":1773822858000},"page":"114542","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Graph structure consistency and pseudo-label guided source-free domain adaptation for lithology identification"],"prefix":"10.1016","volume":"174","author":[{"given":"Jian","family":"Sun","sequence":"first","affiliation":[]},{"given":"Xin","family":"Sha","sequence":"additional","affiliation":[]},{"given":"Rongjun","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Long","family":"Ren","sequence":"additional","affiliation":[]},{"given":"Zhe","family":"Zhang","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.engappai.2026.114542_bib1","first-page":"126","article-title":"GTA-Net: generative graph adaptation for unsupervised domain adaptation","volume":"526","author":"Chen","year":"2023","journal-title":"Neurocomputing"},{"key":"10.1016\/j.engappai.2026.114542_bib2","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2023.127190","article-title":"Uncertainty-aware pseudo-label filtering for Source- free unsupervised domain adaptation","volume":"575","author":"Chen","year":"2024","journal-title":"Neurocomputing"},{"issue":"14","key":"10.1016\/j.engappai.2026.114542_bib3","doi-asserted-by":"crossref","first-page":"7923","DOI":"10.3390\/app15147923","article-title":"Identification of complicated lithology with machine learning","volume":"15","author":"Chen","year":"2025","journal-title":"Appl. Sci."},{"key":"10.1016\/j.engappai.2026.114542_bib4","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"7212","article-title":"Source-free domain adaptation via distribution estimation","author":"Ding","year":"2022"},{"key":"10.1016\/j.engappai.2026.114542_bib5","first-page":"2848","article-title":"Confident anchor-induced multi-source free domain adaptation","volume":"34","author":"Dong","year":"2021","journal-title":"Adv. Neural Inf. Process. Syst."},{"issue":"2","key":"10.1016\/j.engappai.2026.114542_bib6","first-page":"1089","article-title":"DynamicGDA: adaptive graph update for domain adaptation in dynamic environments","volume":"54","author":"Fu","year":"2024","journal-title":"IEEE Trans. Cybern."},{"issue":"5","key":"10.1016\/j.engappai.2026.114542_bib7","first-page":"6460","article-title":"Towards accurate and robust domain adaptation under multiple noisy environments","volume":"45","author":"Han","year":"2022","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.engappai.2026.114542_bib8","first-page":"2427","article-title":"Test-time classifier adjustment module for model-agnostic domain generalization","volume":"34","author":"Iwasawa","year":"2021","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.engappai.2026.114542_bib9","doi-asserted-by":"crossref","DOI":"10.1016\/j.cageo.2024.105775","article-title":"Multimodal feature integration network for lithology identification from point cloud data","volume":"194","author":"Jing","year":"2025","journal-title":"Comput. Geosci."},{"key":"10.1016\/j.engappai.2026.114542_bib10","article-title":"G-SFDA: Graph-based source-free domain adaptation via structure consistency","volume":"139","author":"Li","year":"2023","journal-title":"Pattern Recogn."},{"issue":"14","key":"10.1016\/j.engappai.2026.114542_bib11","doi-asserted-by":"crossref","first-page":"322","DOI":"10.1007\/s42452-024-06020-y","article-title":"Study on automatic lithology identification based on convolutional neural network and deep transfer learning","volume":"6","author":"Li","year":"2024","journal-title":"Discov. Appl. Sci."},{"issue":"8","key":"10.1016\/j.engappai.2026.114542_bib12","doi-asserted-by":"crossref","first-page":"5743","DOI":"10.1109\/TPAMI.2024.3370978","article-title":"A comprehensive survey on source-free domain adaptation","volume":"46","author":"Li","year":"2024","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"9","key":"10.1016\/j.engappai.2026.114542_bib13","doi-asserted-by":"crossref","first-page":"11227","DOI":"10.1109\/TITS.2024.3367665","article-title":"Domain adaptive driver distraction detection based on partial feature alignment and confusion-minimized classification","volume":"25","author":"Li","year":"2024","journal-title":"IEEE Trans. Intell. Transport. Syst."},{"key":"10.1016\/j.engappai.2026.114542_bib14","series-title":"International Conference on Machine Learning","first-page":"6028","article-title":"Do we really need to access the source data? Source hypothesis transfer for unsupervised domain adaptation","author":"Liang","year":"2020"},{"key":"10.1016\/j.engappai.2026.114542_bib15","series-title":"Graph Consistency Based Mean-Teaching for Unsupervised Domain Adaptive Person Re-Identification","author":"Liu","year":"2021"},{"issue":"5","key":"10.1016\/j.engappai.2026.114542_bib16","first-page":"2017","article-title":"GraphDA: Graph-based domain adaptation with attention mechanism","volume":"33","author":"Liu","year":"2021","journal-title":"IEEE Transact. Neural Networks Learn. Syst."},{"key":"10.1016\/j.engappai.2026.114542_bib17","doi-asserted-by":"crossref","DOI":"10.1016\/j.cmpb.2021.106530","article-title":"ECSD- Net: a joint optic disc and cup segmentation and glaucoma classification network based on unsupervised domain adaptation","volume":"213","author":"Liu","year":"2022","journal-title":"Comput. Methods Progr. Biomed."},{"key":"10.1016\/j.engappai.2026.114542_bib18","doi-asserted-by":"crossref","DOI":"10.1016\/j.rse.2023.113924","article-title":"Transfer learning in environmental remote sensing","volume":"301","author":"Ma","year":"2024","journal-title":"Rem. Sens. Environ."},{"key":"10.1016\/j.engappai.2026.114542_bib19","article-title":"GLC++: Source- free universal domain adaptation through global-local clustering and contrastive affinity learning","author":"Qu","year":"2024","journal-title":"arXiv preprint arXiv, 2403.14410"},{"key":"10.1016\/j.engappai.2026.114542_bib20","article-title":"Incremental open-set domain adaptation","author":"Rakshit","year":"2024","journal-title":"arXiv preprint arXiv, 2409."},{"issue":"14","key":"10.1016\/j.engappai.2026.114542_bib21","doi-asserted-by":"crossref","first-page":"2434","DOI":"10.3390\/rs17142434","article-title":"A machine learning-based method for lithology identification of outcrops using TLS-Derived spectral and geometric features","volume":"17","author":"Shao","year":"2025","journal-title":"Remote Sens."},{"key":"10.1016\/j.engappai.2026.114542_bib22","article-title":"Source-Free unsupervised domain adaptation with Hypothesis consolidation of Pre- diction rationale","author":"Shu","year":"2024","journal-title":"arXiv preprint arXiv, 2402.01157"},{"key":"10.1016\/j.engappai.2026.114542_bib23","article-title":"Wiser: weak supervision and supervised representation learning to improve drug response prediction in cancer","author":"Shubham","year":"2024","journal-title":"arXiv preprint arXiv, 2405.04078"},{"key":"10.1016\/j.engappai.2026.114542_bib24","article-title":"Unified source-free domain adaptation","author":"Tang","year":"2024","journal-title":"arXiv preprint arXiv, 2403.07601"},{"issue":"4","key":"10.1016\/j.engappai.2026.114542_bib25","first-page":"6948","article-title":"Graph convolutional domain adaptation for semi-supervised learning","volume":"34","author":"Wang","year":"2020","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"key":"10.1016\/j.engappai.2026.114542_bib26","article-title":"Generalizing segmentation foundation model under sim-to-real domain-shift for guidewire segmentation in X-ray fluoroscopy","author":"Wen","year":"2024","journal-title":"arXiv preprint arXiv, 2410."},{"issue":"2","key":"10.1016\/j.engappai.2026.114542_bib27","doi-asserted-by":"crossref","first-page":"1135","DOI":"10.1016\/j.petsci.2023.09.011","article-title":"A real-time intelligent lithology identification method based on a dynamic felling strategy weighted random forest algorithm","volume":"21","author":"Yan","year":"2024","journal-title":"Pet. Sci."},{"key":"10.1016\/j.engappai.2026.114542_bib28","first-page":"5802","article-title":"Attracting and dispersing: a simple approach for source-free domain adaptation","volume":"35","author":"Yang","year":"2022","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.engappai.2026.114542_bib29","first-page":"5812","article-title":"Graph contrastive learning with augmentations","volume":"33","author":"You","year":"2020","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.engappai.2026.114542_bib30","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"14567","article-title":"DomainGNN: Cross-domain graph matching for unsupervised domain adaptation","author":"Zhang","year":"2022"},{"key":"10.1016\/j.engappai.2026.114542_bib31","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2023.126921","article-title":"Source-free unsupervised domain adaptation: Cur- rent research and future directions","volume":"564","author":"Zhang","year":"2024","journal-title":"Neurocomputing"},{"key":"10.1016\/j.engappai.2026.114542_bib32","doi-asserted-by":"crossref","first-page":"7019","DOI":"10.1109\/TCSVT.2022.3179021","article-title":"Source-free open compound domain adaptation in semantic segmentation","volume":"32","author":"Zhao","year":"2022","journal-title":"IEEE Trans. Circ. Syst. Video Technol."},{"key":"10.1016\/j.engappai.2026.114542_bib33","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2023.122807","article-title":"A comparison review of transfer learning and self-supervised learning: definitions, applications, advantages and limitations","volume":"242","author":"Zhao","year":"2024","journal-title":"Expert Syst. Appl."},{"issue":"3","key":"10.1016\/j.engappai.2026.114542_bib34","first-page":"2890","article-title":"Graph-FreeSFDA: Self-supervised structure learning for source-free domain adaptation","volume":"54","author":"Zhao","year":"2024","journal-title":"Appl. Intell."},{"key":"10.1016\/j.engappai.2026.114542_bib35","series-title":"Proceedings of the International Conference on Machine Learning","first-page":"26345","article-title":"OpenGDA: open set domain adaptation via graph decomposition","author":"Zhou","year":"2023"},{"issue":"3","key":"10.1016\/j.engappai.2026.114542_bib36","first-page":"3852","article-title":"SRoUDA: meta self-training for robust unsupervised domain adaptation","volume":"37","author":"Zhu","year":"2023","journal-title":"Proc. AAAI Conf. Artif. Intell."}],"container-title":["Engineering Applications of Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0952197626008237?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0952197626008237?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T03:02:41Z","timestamp":1776135761000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0952197626008237"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6]]},"references-count":36,"alternative-id":["S0952197626008237"],"URL":"https:\/\/doi.org\/10.1016\/j.engappai.2026.114542","relation":{},"ISSN":["0952-1976"],"issn-type":[{"value":"0952-1976","type":"print"}],"subject":[],"published":{"date-parts":[[2026,6]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Graph structure consistency and pseudo-label guided source-free domain adaptation for lithology identification","name":"articletitle","label":"Article Title"},{"value":"Engineering Applications of Artificial Intelligence","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.engappai.2026.114542","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Authors. Published by Elsevier Ltd.","name":"copyright","label":"Copyright"}],"article-number":"114542"}}