{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T12:07:43Z","timestamp":1784203663266,"version":"3.55.0"},"reference-count":46,"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"}],"funder":[{"DOI":"10.13039\/501100019534","name":"Science Fund for Distinguished Young Scholars of Guangxi Province","doi-asserted-by":"publisher","award":["2021GXNSFFA220004"],"award-info":[{"award-number":["2021GXNSFFA220004"]}],"id":[{"id":"10.13039\/501100019534","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62261014"],"award-info":[{"award-number":["62261014"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"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.2026.134105","type":"journal-article","created":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T06:50:09Z","timestamp":1780037409000},"page":"134105","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Heterogeneous change detection based on symmetric transformer graph convolution network"],"prefix":"10.1016","volume":"696","author":[{"given":"Yongxin","family":"Hu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junzheng","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-1290-6565","authenticated-orcid":false,"given":"Jichao","family":"Yao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.neucom.2026.134105_bib0005","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/LGRS.2020.3041409","article-title":"Simple multiscale unet for change detection with heterogeneous remote sensing images","volume":"19","author":"Zhiyong","year":"2022","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"issue":"1","key":"10.1016\/j.neucom.2026.134105_bib0010","doi-asserted-by":"crossref","DOI":"10.1080\/15481603.2023.2220525","article-title":"Hybrid approach using deep learning and graph comparison for building change detection","volume":"60","author":"Park","year":"2023","journal-title":"Giscience Remote Sens."},{"issue":"1","key":"10.1016\/j.neucom.2026.134105_bib0015","doi-asserted-by":"crossref","first-page":"1685","DOI":"10.1080\/17538947.2023.2210311","article-title":"Gmts: Gnn-based multi-scale transformer siamese network for remote sensing building change detection","volume":"16","author":"Song","year":"2023","journal-title":"Int. J. Digit. Earth"},{"key":"10.1016\/j.neucom.2026.134105_bib0020","first-page":"1","article-title":"Change alignment-based graph structure learning for unsupervised heterogeneous change detection","volume":"20","author":"Xiao","year":"2023","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"issue":"111664","key":"10.1016\/j.neucom.2026.134105_bib0025","article-title":"Rapid and robust monitoring of flood events using sentinel-1 and landsat data on the google earth engine","volume":"240","author":"DeVries","year":"2020","journal-title":"Remote Sens. Environ."},{"issue":"12","key":"10.1016\/j.neucom.2026.134105_bib0030","doi-asserted-by":"crossref","DOI":"10.3390\/w15122182","article-title":"Spatial evaluation of a natural flood management project using sar change detection","volume":"15","author":"Jarrett","year":"2023","journal-title":"Water"},{"key":"10.1016\/j.neucom.2026.134105_bib0035","first-page":"1","article-title":"Landslide inventory mapping on vhr images via adaptive region shape similarity","volume":"60","author":"Zhiyong","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"11","key":"10.1016\/j.neucom.2026.134105_bib0040","doi-asserted-by":"crossref","DOI":"10.3390\/rs15112889","article-title":"Consensus techniques for unsupervised binary change detection using multi-scale segmentation detectors for land cover vegetation images","volume":"15","author":"Cardama","year":"2023","journal-title":"Remote Sens."},{"issue":"5","key":"10.1016\/j.neucom.2026.134105_bib0045","doi-asserted-by":"crossref","first-page":"699","DOI":"10.1080\/15481603.2018.1550245","article-title":"Reducing the effects of vegetation phenology on change detection in tropical seasonal biomes","volume":"56","author":"de Oliveira Silveira","year":"2019","journal-title":"Giscience Remote Sens."},{"issue":"9","key":"10.1016\/j.neucom.2026.134105_bib0050","doi-asserted-by":"crossref","DOI":"10.3390\/rs15092464","article-title":"Signet: A siamese graph convolutional network for multi-class urban change detection","volume":"15","author":"Zhou","year":"2023","journal-title":"Remote Sens."},{"issue":"12","key":"10.1016\/j.neucom.2026.134105_bib0055","doi-asserted-by":"crossref","first-page":"9941","DOI":"10.1109\/TGRS.2019.2930322","article-title":"An object-based hierarchical compound classification method for change detection in heterogeneous optical and sar images","volume":"57","author":"Wan","year":"2019","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.neucom.2026.134105_bib0060","first-page":"1","article-title":"Hierarchical Attention Feature Fusion-Based Network for Land Cover Change Detection With Homogeneous and Heterogeneous Remote Sensing Images","volume":"61","author":"Zhiyong","year":"2023","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.neucom.2026.134105_bib0065","first-page":"1","article-title":"WaveHFG: High-Frequency Guidance for Heterogeneous Remote Sensing Image Change Detection With Wavelet Features","volume":"64","author":"Song","year":"2026","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"4","key":"10.1016\/j.neucom.2026.134105_bib0070","doi-asserted-by":"crossref","first-page":"1822","DOI":"10.1109\/TIP.2017.2784560","article-title":"Change detection in heterogenous remote sensing images via homogeneous pixel transformation","volume":"27","author":"Liu","year":"2018","journal-title":"IEEE Trans. Image Process."},{"issue":"12","key":"10.1016\/j.neucom.2026.134105_bib0075","doi-asserted-by":"crossref","first-page":"9960","DOI":"10.1109\/TGRS.2019.2930348","article-title":"Unsupervised image regression for heterogeneous change detection","volume":"57","author":"Luppino","year":"2019","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.neucom.2026.134105_bib0080","first-page":"1","article-title":"Sparse-constrained adaptive structure consistency-based unsupervised image regression for heterogeneous remote-sensing change detection","volume":"60","author":"Sun","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"11","key":"10.1016\/j.neucom.2026.134105_bib0085","doi-asserted-by":"crossref","first-page":"8046","DOI":"10.1109\/TGRS.2020.2986239","article-title":"A fractal projection and markovian segmentation-based approach for multimodal change detection","volume":"58","author":"Mignotte","year":"2020","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"3","key":"10.1016\/j.neucom.2026.134105_bib0090","doi-asserted-by":"crossref","first-page":"799","DOI":"10.1109\/TIP.2014.2387013","article-title":"A new multivariate statistical model for change detection in images acquired by homogeneous and heterogeneous sensors","volume":"24","author":"Prendes","year":"2015","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.neucom.2026.134105_bib0095","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1016\/j.isprsjprs.2015.02.005","article-title":"Spectral alignment of multi-temporal cross-sensor images with automated kernel canonical correlation analysis","volume":"107","author":"Volpi","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"issue":"2","key":"10.1016\/j.neucom.2026.134105_bib0100","doi-asserted-by":"crossref","first-page":"1046","DOI":"10.1109\/TGRS.2017.2758359","article-title":"An energy-based model encoding nonlocal pairwise pixel interactions for multisensor change detection","volume":"56","author":"Touati","year":"2018","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"1","key":"10.1016\/j.neucom.2026.134105_bib0105","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1109\/TNNLS.2022.3172183","article-title":"Code-Aligned Autoencoders for Unsupervised Change Detection in Multimodal Remote Sensing Images","volume":"35","author":"Luppino","year":"2024","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"issue":"102313","key":"10.1016\/j.neucom.2026.134105_bib0110","doi-asserted-by":"crossref","DOI":"10.1007\/978-981-97-5208-9","article-title":"CD-GAN: A robust fusion-based generative adversarial network for unsupervised remote sensing change detection with heterogeneous sensors","volume":"107","author":"Wang","year":"2024","journal-title":"Inf. Fusion"},{"key":"10.1016\/j.neucom.2026.134105_bib0115","first-page":"1","article-title":"Aekan: Exploring superpixel-based autoencoder kolmogorov-arnold network for unsupervised multimodal change detection","volume":"63","author":"Liu","year":"2025","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.neucom.2026.134105_bib0120","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1016\/j.isprsjprs.2023.03.004","article-title":"Fourier domain structural relationship analysis for unsupervised multimodal change detection","volume":"198","author":"Chen","year":"2023","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"10.1016\/j.neucom.2026.134105_bib0125","doi-asserted-by":"crossref","first-page":"487","DOI":"10.1016\/j.isprsjprs.2026.02.004","article-title":"Multimodal remote sensing change detection: An image matching perspective","volume":"233","author":"Chen","year":"2026","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"issue":"102615","key":"10.1016\/j.neucom.2026.134105_bib0130","article-title":"A multiscale graph convolutional network for change detection in homogeneous and heterogeneous remote sensing images","volume":"105","author":"Junzheng","year":"2021","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"issue":"17","key":"10.1016\/j.neucom.2026.134105_bib0135","doi-asserted-by":"crossref","DOI":"10.3390\/rs12172683","article-title":"Graph-based data fusion applied to: Change detection and biomass estimation in rice crops","volume":"12","author":"Jimenez-Sierra","year":"2020","journal-title":"Remote Sens."},{"key":"10.1016\/j.neucom.2026.134105_bib0140","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TGRS.2022.3168126","article-title":"Graph learning based on signal smoothness representation for homogeneous and heterogeneous change detection","volume":"60","author":"Jimenez-Sierra","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"107598","key":"10.1016\/j.neucom.2026.134105_bib0145","article-title":"Nonlocal patch similarity based heterogeneous remote sensing change detection","volume":"109","author":"Sun","year":"2021","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.neucom.2026.134105_bib0150","first-page":"1","article-title":"Structure consistency-based graph for unsupervised change detection with homogeneous and heterogeneous remote sensing images","volume":"60","author":"Sun","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.neucom.2026.134105_bib0155","doi-asserted-by":"crossref","first-page":"6277","DOI":"10.1109\/TIP.2021.3093766","article-title":"Iterative robust graph for unsupervised change detection of heterogeneous remote sensing images","volume":"30","author":"Sun","year":"2021","journal-title":"IEEE Trans. Image Process."},{"issue":"2","key":"10.1016\/j.neucom.2026.134105_bib0160","doi-asserted-by":"crossref","first-page":"1613","DOI":"10.1109\/TNNLS.2022.3184414","article-title":"Image regression with structure cycle consistency for heterogeneous change detection","volume":"35","author":"Sun","year":"2024","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"issue":"112394","key":"10.1016\/j.neucom.2026.134105_bib0165","article-title":"A graph contrastive learning network for change detection with heterogeneous remote sensing images","volume":"172","author":"Zhiyong","year":"2026","journal-title":"Pattern Recognit."},{"issue":"112394","key":"10.1016\/j.neucom.2026.134105_bib0170","article-title":"A graph contrastive learning network for change detection with heterogeneous remote sensing images","volume":"172","author":"Zhiyong","year":"2026","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.neucom.2026.134105_bib0175","first-page":"1","article-title":"Sdc-gae: Structural difference compensation graph autoencoder for unsupervised multimodal change detection","volume":"62","author":"Han","year":"2024","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.neucom.2026.134105_bib0180","first-page":"1","article-title":"Unsupervised multimodal change detection based on structural relationship graph representation learning","volume":"60","author":"Chen","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.neucom.2026.134105_bib0185","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TAES.2026.3711576","article-title":"Cross-Cycle Structured Graph Autoencoder for Unsupervised Cross-Sensor Image Change Detection","author":"Huang","year":"2026","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"issue":"3","key":"10.1016\/j.neucom.2026.134105_bib0190","doi-asserted-by":"crossref","first-page":"545","DOI":"10.1109\/TNNLS.2016.2636227","article-title":"A deep convolutional coupling network for change detection based on heterogeneous optical and radar images","volume":"29","author":"Liu","year":"2018","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"10.1016\/j.neucom.2026.134105_bib0195","doi-asserted-by":"crossref","first-page":"399","DOI":"10.4153\/CJM-1956-045-5","article-title":"Maximal flow through a network","volume":"8","author":"Ford","year":"1956","journal-title":"Can. J. Math."},{"key":"10.1016\/j.neucom.2026.134105_bib0200","first-page":"1","article-title":"Graph signal processing for heterogeneous change detection","volume":"60","author":"Sun","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"1","key":"10.1016\/j.neucom.2026.134105_bib0205","doi-asserted-by":"crossref","first-page":"331","DOI":"10.1109\/JSTARS.2011.2179638","article-title":"Multi-modal change detection, application to the detection of flooded areas: Outcome of the 2009\u20132010 data fusion contest","volume":"5","author":"Longbotham","year":"2012","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"10.1016\/j.neucom.2026.134105_bib0210","first-page":"1","article-title":"Graph Signal Processing for Heterogeneous Change Detection","volume":"60","author":"Sun","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"107598","key":"10.1016\/j.neucom.2026.134105_bib0215","article-title":"Nonlocal patch similarity based heterogeneous remote sensing change detection","volume":"109","author":"Sun","year":"2021","journal-title":"Pattern Recognit."},{"issue":"6","key":"10.1016\/j.neucom.2026.134105_bib0220","doi-asserted-by":"crossref","first-page":"4841","DOI":"10.1109\/TGRS.2020.3013673","article-title":"Patch Similarity Graph Matrix-Based Unsupervised Remote Sensing Change Detection With Homogeneous and Heterogeneous Sensors","volume":"59","author":"Sun","year":"2021","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.neucom.2026.134105_bib0225","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TGRS.2021.3056196","article-title":"Deep Image Translation With an Affinity-Based Change Prior for Unsupervised Multimodal Change Detection","volume":"60","author":"Luppino","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.neucom.2026.134105_bib0230","doi-asserted-by":"crossref","first-page":"396","DOI":"10.1016\/j.isprsjprs.2025.05.029","article-title":"GLCD-DA: Change detection from optical and SAR imagery using a Global-Local network with diversified attention","volume":"226","author":"Jie","year":"2025","journal-title":"ISPRS J. Photogramm. Remote Sens."}],"container-title":["Neurocomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0925231226015031?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0925231226015031?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T11:43:31Z","timestamp":1784202211000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0925231226015031"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10]]},"references-count":46,"alternative-id":["S0925231226015031"],"URL":"https:\/\/doi.org\/10.1016\/j.neucom.2026.134105","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":"Heterogeneous change detection based on symmetric transformer graph convolution network","name":"articletitle","label":"Article Title"},{"value":"Neurocomputing","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.neucom.2026.134105","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":"134105"}}