{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,11]],"date-time":"2026-07-11T20:13:21Z","timestamp":1783800801541,"version":"3.55.0"},"reference-count":55,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52571332"],"award-info":[{"award-number":["52571332"]}],"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":[[2026,11]]},"DOI":"10.1016\/j.neucom.2026.134441","type":"journal-article","created":{"date-parts":[[2026,7,6]],"date-time":"2026-07-06T15:51:32Z","timestamp":1783353092000},"page":"134441","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["SFC-net: A spatial frequency-inspired feature collaborative alignment and fusion network for weakly aligned RGB-T salient object detection"],"prefix":"10.1016","volume":"700","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-2926-7413","authenticated-orcid":false,"given":"Jubo","family":"Chen","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3218-1486","authenticated-orcid":false,"given":"Xiaosheng","family":"Yu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-9327-3183","authenticated-orcid":false,"given":"Liuyi","family":"Meng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-6777-3005","authenticated-orcid":false,"given":"Yangpu","family":"Tang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1399-314X","authenticated-orcid":false,"given":"Mingli","family":"Song","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"3","key":"10.1016\/j.neucom.2026.134441_bib0005","doi-asserted-by":"crossref","first-page":"1224","DOI":"10.1109\/TCSVT.2021.3077058","article-title":"ECFFNet: Effective and consistent feature fusion network for RGB-T salient object detection","volume":"32","author":"Zhou","year":"2021","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"issue":"4","key":"10.1016\/j.neucom.2026.134441_bib0010","doi-asserted-by":"crossref","first-page":"2091","DOI":"10.1109\/TCSVT.2021.3082939","article-title":"Unified information fusion network for multi-modal RGB-D and RGB-T salient object detection","volume":"32","author":"Gao","year":"2021","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.neucom.2026.134441_bib0015","doi-asserted-by":"crossref","first-page":"6971","DOI":"10.1109\/TMM.2022.3216476","article-title":"Does thermal really always matter for RGB-T salient object detection?","volume":"25","author":"Cong","year":"2022","journal-title":"IEEE Trans. Multimed."},{"issue":"2","key":"10.1016\/j.neucom.2026.134441_bib0020","doi-asserted-by":"crossref","first-page":"273","DOI":"10.26599\/CVM.2025.9450501","article-title":"A comprehensive survey on the research and development of RGB-T salient object detection","volume":"12","author":"Hou","year":"2026","journal-title":"Comput. Vis. Media"},{"issue":"9","key":"10.1016\/j.neucom.2026.134441_bib0025","doi-asserted-by":"crossref","first-page":"4401","DOI":"10.1109\/TIP.2019.2908802","article-title":"Enhance visual recognition under adverse conditions via deep networks","volume":"28","author":"Liu","year":"2019","journal-title":"IEEE Trans. Image Process."},{"issue":"11","key":"10.1016\/j.neucom.2026.134441_bib0030","doi-asserted-by":"crossref","first-page":"2278","DOI":"10.1109\/5.726791","article-title":"Gradient-based learning applied to document recognition","volume":"86","author":"LeCun","year":"2002","journal-title":"Proc. IEEE"},{"key":"10.1016\/j.neucom.2026.134441_bib0035","series-title":"Proceedings of the IEEE conference on computer vision and pattern recognition","first-page":"770","article-title":"Deep residual learning for image recognition","author":"He","year":"2016"},{"key":"10.1016\/j.neucom.2026.134441_bib0040","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2024.112262","article-title":"Feature radiance fields (FeRF): A multi-level feature fusion method with deep neural network for image synthesis","volume":"167","author":"Chen","year":"2024","journal-title":"Appl. Soft Comput."},{"key":"10.1016\/j.neucom.2026.134441_bib0045","author":"Dosovitskiy"},{"key":"10.1016\/j.neucom.2026.134441_bib0050","series-title":"Proceedings of the IEEE\/CVF international conference on computer vision","first-page":"10012","article-title":"Swin transformer: Hierarchical vision transformer using shifted windows","author":"Liu","year":"2021"},{"key":"10.1016\/j.neucom.2026.134441_bib0055","series-title":"Proceedings of the IEEE conference on computer vision and pattern recognition","first-page":"2161","article-title":"A solution for multi-alignment by transformation synchronisation","author":"Bernard","year":"2015"},{"key":"10.1016\/j.neucom.2026.134441_bib0060","series-title":"Proceedings of the IEEE international conference on computer vision","first-page":"764","article-title":"Deformable convolutional networks","author":"Dai","year":"2017"},{"key":"10.1016\/j.neucom.2026.134441_bib0065","series-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","first-page":"5513","article-title":"Unireplknet: A universal perception large-kernel convnet for audio video point cloud time-series and image recognition","author":"Ding","year":"2024"},{"key":"10.1016\/j.neucom.2026.134441_bib0070","series-title":"Proceedings of the IEEE\/CVF international conference on computer vision","first-page":"3435","article-title":"Drop an octave: Reducing spatial redundancy in convolutional neural networks with octave convolution","author":"Chen","year":"2019"},{"key":"10.1016\/j.neucom.2026.134441_bib0075","doi-asserted-by":"crossref","first-page":"3752","DOI":"10.1109\/TIP.2022.3176540","article-title":"Weakly alignment-free RGBT salient object detection with deep correlation network","volume":"31","author":"Tu","year":"2022","journal-title":"IEEE Trans. Image Process."},{"issue":"9","key":"10.1016\/j.neucom.2026.134441_bib0080","doi-asserted-by":"crossref","first-page":"1555","DOI":"10.3390\/math10091555","article-title":"EADN: An efficient deep learning model for anomaly detection in videos","volume":"10","author":"Ul Amin","year":"2022","journal-title":"Mathematics"},{"key":"10.1016\/j.neucom.2026.134441_bib0085","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2025.111655","article-title":"Enhancing pine wilt disease detection with synthetic data and external attention-based transformers","volume":"159","author":"Amin","year":"2025","journal-title":"Eng. Appl. Artif. Intell."},{"issue":"11","key":"10.1016\/j.neucom.2026.134441_bib0090","doi-asserted-by":"crossref","first-page":"3212","DOI":"10.1109\/TNNLS.2018.2876865","article-title":"Object detection with deep learning: A review","volume":"30","author":"Zhao","year":"2019","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"10.1016\/j.neucom.2026.134441_bib0095","doi-asserted-by":"crossref","first-page":"1329","DOI":"10.1109\/TIP.2023.3242775","article-title":"LSNet: Lightweight spatial boosting network for detecting salient objects in RGB-thermal images","volume":"32","author":"Zhou","year":"2023","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.neucom.2026.134441_bib0100","doi-asserted-by":"crossref","first-page":"410","DOI":"10.1016\/j.neunet.2023.12.031","article-title":"MSEDNet: Multi-scale fusion and edge-supervised network for RGB-T salient object detection","volume":"171","author":"Peng","year":"2024","journal-title":"Neural Netw."},{"issue":"8","key":"10.1016\/j.neucom.2026.134441_bib0105","doi-asserted-by":"crossref","first-page":"7344","DOI":"10.1109\/TCSVT.2024.3375505","article-title":"Learning adaptive fusion bank for multi-modal salient object detection","volume":"34","author":"Wang","year":"2024","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"issue":"3","key":"10.1016\/j.neucom.2026.134441_bib0110","doi-asserted-by":"crossref","first-page":"1958","DOI":"10.1109\/TPAMI.2024.3511621","article-title":"Divide-and-conquer: Confluent triple-flow network for RGB-T salient object detection","volume":"47","author":"Tang","year":"2024","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.neucom.2026.134441_bib0115","series-title":"Chinese Conference on Image and Graphics Technologies","first-page":"359","article-title":"RGB-T saliency detection benchmark: Dataset, baselines, analysis and a novel approach","author":"Wang","year":"2018"},{"issue":"1","key":"10.1016\/j.neucom.2026.134441_bib0120","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1109\/TMM.2019.2924578","article-title":"RGB-T image saliency detection via collaborative graph learning","volume":"22","author":"Tu","year":"2019","journal-title":"IEEE Trans. Multimed."},{"key":"10.1016\/j.neucom.2026.134441_bib0125","doi-asserted-by":"crossref","first-page":"4163","DOI":"10.1109\/TMM.2022.3171688","article-title":"RGBT salient object detection: A large-scale dataset and benchmark","volume":"25","author":"Tu","year":"2022","journal-title":"IEEE Trans. Multimed."},{"key":"10.1016\/j.neucom.2026.134441_bib0130","first-page":"1","article-title":"Modality registration and object search framework for UAV-based unregistered RGB-T image salient object detection","volume":"61","author":"Song","year":"2023","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"4","key":"10.1016\/j.neucom.2026.134441_bib0135","doi-asserted-by":"crossref","first-page":"3104","DOI":"10.1109\/TCSVT.2024.3502244","article-title":"Highly efficient RGB-D salient object detection with adaptive fusion and attention regulation","volume":"35","author":"Gao","year":"2024","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.neucom.2026.134441_bib0140","first-page":"1","article-title":"Efficient fourier filtering network with contrastive learning for uav-based unaligned bi-modal salient object detection","volume":"63","author":"Lyu","year":"2025","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.neucom.2026.134441_bib0145","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2023.120391","article-title":"Deep learning based active learning technique for data annotation and improve the overall performance of classification models","volume":"228","author":"Amin","year":"2023","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.neucom.2026.134441_bib0150","article-title":"A comprehensive approach for image quality assessment using quality-centric embedding and ranking networks","author":"Haider","year":"2025","journal-title":"Pattern Recognit."},{"issue":"4","key":"10.1016\/j.neucom.2026.134441_bib0155","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1016\/0165-1684(90)90158-U","article-title":"Fast Fourier transforms: a tutorial review and a state of the art","volume":"19","author":"Duhamel","year":"1990","journal-title":"Signal Process."},{"key":"10.1016\/j.neucom.2026.134441_bib0160","series-title":"IOP Conference Series: Materials Science and Engineering, 557","article-title":"Image enhancement based on discrete cosine transforms (DCT) and discrete wavelet transform (DWT): A review","author":"Azani Mustafa","year":"2019"},{"key":"10.1016\/j.neucom.2026.134441_bib0165","doi-asserted-by":"crossref","first-page":"58869","DOI":"10.1109\/ACCESS.2022.3179517","article-title":"A review of wavelet analysis and its applications: Challenges and opportunities","volume":"10","author":"Guo","year":"2022","journal-title":"IEEE Access"},{"key":"10.1016\/j.neucom.2026.134441_bib0170","article-title":"A Spatial-spectral Multi-view Contrastive Learning Framework for Scene Representation Learning","author":"Chen","year":"2025","journal-title":"Inf. Fusion"},{"issue":"4","key":"10.1016\/j.neucom.2026.134441_bib0175","doi-asserted-by":"crossref","first-page":"11791","DOI":"10.1109\/TCE.2025.3624269","article-title":"Idea Visual: Intent-Driven View Synthesis for Smart Mobile Devices via Retrieval-Augmented Diffusion Models","volume":"71","author":"Chen","year":"2025","journal-title":"IEEE Trans. Consum. Electron."},{"issue":"1","key":"10.1016\/j.neucom.2026.134441_bib0180","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1186\/s42492-019-0016-7","article-title":"Brief review of image denoising techniques","volume":"2","author":"Fan","year":"2019","journal-title":"Vis. comput. ind. biomed. art"},{"issue":"3","key":"10.1016\/j.neucom.2026.134441_bib0185","doi-asserted-by":"crossref","first-page":"329","DOI":"10.1007\/s11760-010-0204-6","article-title":"A survey on super-resolution imaging","volume":"5","author":"Tian","year":"2011","journal-title":"Signal Image Video Process."},{"issue":"2","key":"10.1016\/j.neucom.2026.134441_bib0190","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1007\/s41095-019-0149-9","article-title":"Salient object detection: A survey","volume":"5","author":"Borji","year":"2019","journal-title":"Comput. Vis. Media"},{"issue":"1","key":"10.1016\/j.neucom.2026.134441_bib0195","doi-asserted-by":"crossref","first-page":"883","DOI":"10.1109\/TCE.2024.3502692","article-title":"A dual-stream cross-domain integration network for RGB-T salient object detection","volume":"71","author":"Yu","year":"2024","journal-title":"IEEE Trans. Consum. Electron."},{"issue":"2","key":"10.1016\/j.neucom.2026.134441_bib0200","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1007\/s00371-026-04359-4","article-title":"A dual-branch RGB-T salient object detection via spatial-frequency integration: X. Yu et al","volume":"42","author":"Yu","year":"2026","journal-title":"Vis. Comput."},{"issue":"1","key":"10.1016\/j.neucom.2026.134441_bib0205","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1007\/s10479-005-5724-z","article-title":"A tutorial on the cross-entropy method","volume":"134","author":"De Boer","year":"2005","journal-title":"Ann. Oper. Res."},{"key":"10.1016\/j.neucom.2026.134441_bib0210","series-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","first-page":"658","article-title":"Generalized intersection over union: A metric and a loss for bounding box regression","author":"Rezatofighi","year":"2019"},{"key":"10.1016\/j.neucom.2026.134441_bib0215","author":"Ba"},{"key":"10.1016\/j.neucom.2026.134441_bib0220","series-title":"International conference on machine learning","first-page":"448","article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","author":"Ioffe","year":"2015"},{"key":"10.1016\/j.neucom.2026.134441_bib0225","author":"Agarap"},{"key":"10.1016\/j.neucom.2026.134441_bib0230","series-title":"Computational intelligence: a methodological introduction","first-page":"53","article-title":"Multi-layer perceptrons","author":"Kruse","year":"2022"},{"key":"10.1016\/j.neucom.2026.134441_bib0235","series-title":"Proceedings of the AAAI Conference on Artificial Intelligence, 40","first-page":"12259","article-title":"Strip R-CNN: large strip convolution for remote sensing object detection","author":"Yuan","year":"2026"},{"key":"10.1016\/j.neucom.2026.134441_bib0240","article-title":"Pytorch: An imperative style, high-performance deep learning library","volume":"32","author":"Paszke","year":"2019","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.neucom.2026.134441_bib0245","series-title":"2009 IEEE conference on computer vision and pattern recognition","first-page":"248","article-title":"Imagenet: A large-scale hierarchical image database","author":"Deng","year":"2009"},{"key":"10.1016\/j.neucom.2026.134441_bib0250","author":"Loshchilov"},{"key":"10.1016\/j.neucom.2026.134441_bib0255","author":"Fan"},{"key":"10.1016\/j.neucom.2026.134441_bib0260","series-title":"Proceedings of the IEEE international conference on computer vision","first-page":"4548","article-title":"Structure-measure: A new way to evaluate foreground maps","author":"Fan","year":"2017"},{"key":"10.1016\/j.neucom.2026.134441_bib0265","series-title":"2009 IEEE conference on computer vision and pattern recognition","first-page":"1597","article-title":"Frequency-tuned salient region detection","author":"Achanta","year":"2009"},{"key":"10.1016\/j.neucom.2026.134441_bib0270","author":"Simonyan"},{"key":"10.1016\/j.neucom.2026.134441_bib0275","doi-asserted-by":"crossref","first-page":"10692","DOI":"10.1109\/TMM.2024.3410542","article-title":"Alignment-free rgbt salient object detection: Semantics-guided asymmetric correlation network and a unified benchmark","volume":"26","author":"Wang","year":"2024","journal-title":"IEEE Trans. Multimed."}],"container-title":["Neurocomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0925231226018394?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0925231226018394?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,11]],"date-time":"2026-07-11T19:37:09Z","timestamp":1783798629000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0925231226018394"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,11]]},"references-count":55,"alternative-id":["S0925231226018394"],"URL":"https:\/\/doi.org\/10.1016\/j.neucom.2026.134441","relation":{},"ISSN":["0925-2312"],"issn-type":[{"value":"0925-2312","type":"print"}],"subject":[],"published":{"date-parts":[[2026,11]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"SFC-net: A spatial frequency-inspired feature collaborative alignment and fusion network for weakly aligned RGB-T salient object detection","name":"articletitle","label":"Article Title"},{"value":"Neurocomputing","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.neucom.2026.134441","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":"134441"}}