{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,13]],"date-time":"2026-06-13T00:56:37Z","timestamp":1781312197597,"version":"3.54.1"},"reference-count":62,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100013141","name":"Jilin Provincial Key Research and Development Plan Project","doi-asserted-by":"publisher","award":["20260203072SF"],"award-info":[{"award-number":["20260203072SF"]}],"id":[{"id":"10.13039\/501100013141","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Expert Systems with Applications"],"published-print":{"date-parts":[[2026,8]]},"DOI":"10.1016\/j.eswa.2026.132297","type":"journal-article","created":{"date-parts":[[2026,4,6]],"date-time":"2026-04-06T23:14:09Z","timestamp":1775517249000},"page":"132297","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["DIGWO_BS: a hyperspectral band selection optimization framework for preserving spectral structure"],"prefix":"10.1016","volume":"322","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-6008-0776","authenticated-orcid":false,"given":"Yihong","family":"Bai","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dong","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ali Asghar","family":"Heidari","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhennao","family":"Cai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4698-2965","authenticated-orcid":false,"given":"Lei","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7714-9693","authenticated-orcid":false,"given":"Huiling","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.eswa.2026.132297_b0005","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2024.109847","article-title":"An overview of recent advancements in hyperspectral imaging in the egg and hatchery industry","volume":"230","author":"Ahmed","year":"2025","journal-title":"Computers and Electronics in Agriculture"},{"issue":"6","key":"10.1016\/j.eswa.2026.132297_b0010","doi-asserted-by":"crossref","first-page":"2631","DOI":"10.1109\/36.803411","article-title":"A joint band prioritization and band-decorrelation approach to band selection for hyperspectral image classification","volume":"37","author":"Chang","year":"1999","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"key":"10.1016\/j.eswa.2026.132297_b0015","doi-asserted-by":"crossref","unstructured":"Cherifi, M., Mesloub, A., El Korso, M. N., Touhami, T., & Gharbi, A. H. (2024). Dimensionality reduction for hyperspectral image classification. 2024 8th International Conference on Image and Signal Processing and their Applications (ISPA) (pp. 1-8). IEEE.","DOI":"10.1109\/ISPA59904.2024.10536775"},{"key":"10.1016\/j.eswa.2026.132297_b0020","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2024.106982","article-title":"Involution-based HarmonyNet: An efficient hyperspectral imaging model for automatic detection of neonatal health status","volume":"100","author":"Cihan","year":"2025","journal-title":"Biomedical Signal Processing and Control"},{"key":"10.1016\/j.eswa.2026.132297_b0025","doi-asserted-by":"crossref","unstructured":"Congalton, R. G., & Green, K. (2019). Assessing the accuracy of remotely sensed data: principles and practices. CRC Press.","DOI":"10.1201\/9780429052729"},{"key":"10.1016\/j.eswa.2026.132297_b0030","doi-asserted-by":"crossref","unstructured":"Deepa, P., & Thilagavathi, K. (2015). Feature extraction of hyperspectral image using principal component analysis and folded-principal component analysis. 2015 2nd International Conference on Electronics and Communication Systems (ICECS) (pp. 656-660). IEEE.","DOI":"10.1109\/ECS.2015.7124989"},{"key":"10.1016\/j.eswa.2026.132297_b0035","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2022.110011","article-title":"Coati Optimization Algorithm: A new bio-inspired metaheuristic algorithm for solving optimization problems","volume":"259","author":"Dehghani","year":"2023","journal-title":"Knowledge-based systems"},{"key":"10.1016\/j.eswa.2026.132297_b0040","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2021.107574","article-title":"Nonlinear-based chaotic Harris hawks optimizer: Algorithm and internet of vehicles application","volume":"109","author":"Dehkordi","year":"2021","journal-title":"Applied Soft Computing"},{"key":"10.1016\/j.eswa.2026.132297_b0045","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2020.106704","article-title":"A bioinformatic variant fruit fly optimizer for tackling optimization problems","volume":"213","author":"Fan","year":"2021","journal-title":"Knowledge-based Systems"},{"issue":"6","key":"10.1016\/j.eswa.2026.132297_b0050","doi-asserted-by":"crossref","first-page":"2824","DOI":"10.1109\/JSTARS.2015.2441771","article-title":"Fast forward feature selection of hyperspectral images for classification with Gaussian mixture models","volume":"8","author":"Fauvel","year":"2015","journal-title":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"},{"issue":"5","key":"10.1016\/j.eswa.2026.132297_b0055","doi-asserted-by":"crossref","first-page":"2956","DOI":"10.1109\/TGRS.2014.2367022","article-title":"Mutual-information-based semi-supervised hyperspectral band selection with high discrimination, high information, and low redundancy","volume":"53","author":"Feng","year":"2014","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"issue":"6","key":"10.1016\/j.eswa.2026.132297_b0060","doi-asserted-by":"crossref","first-page":"134","DOI":"10.1007\/s10462-024-10716-3","article-title":"Red-billed blue magpie optimizer: A novel metaheuristic algorithm for 2D\/3D UAV path planning and engineering design problems","volume":"57","author":"Fu","year":"2024","journal-title":"Artificial Intelligence Review"},{"issue":"8","key":"10.1016\/j.eswa.2026.132297_b0065","doi-asserted-by":"crossref","first-page":"17955","DOI":"10.1364\/OE.558189","article-title":"Application of hyperspectral imaging in environmental monitoring: Air pollution classification and detection","volume":"33","author":"Huang","year":"2025","journal-title":"Optics Express"},{"issue":"1","key":"10.1016\/j.eswa.2026.132297_b0070","doi-asserted-by":"crossref","first-page":"27662","DOI":"10.1038\/s41598-024-79209-1","article-title":"Comparison of dimensionality reduction methods on hyperspectral images for the identification of heathlands and mires","volume":"14","author":"Jaroci\u0144ska","year":"2024","journal-title":"Scientific Reports"},{"key":"10.1016\/j.eswa.2026.132297_b0075","doi-asserted-by":"crossref","unstructured":"Jena, B., Naik, M. K., & Panda, R. (2023). A novel Kaniadakis entropy-based multilevel thresholding using energy curve and Black Widow optimization algorithm with Gaussian mutation. 2023 International Conference in Advances in Power, Signal, and Information Technology (APSIT) (pp. 86-91). IEEE.","DOI":"10.1109\/APSIT58554.2023.10201718"},{"issue":"12","key":"10.1016\/j.eswa.2026.132297_b0080","doi-asserted-by":"crossref","first-page":"4985","DOI":"10.1109\/JSTARS.2019.2944930","article-title":"An automatic bad band pre-removal method for hyperspectral imagery","volume":"12","author":"Ji","year":"2019","journal-title":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"},{"key":"10.1016\/j.eswa.2026.132297_b0085","series-title":"Particle swarm optimization. Proceedings of ICNN'95-international conference on neural networks","first-page":"1942","author":"Kennedy","year":"1995"},{"key":"10.1016\/j.eswa.2026.132297_b0090","doi-asserted-by":"crossref","unstructured":"Kurra, S., Emani, P. R., Aala, S., & Chinnadurai, S. (2024). A robust dimension reduction technique for hyperspectral blood stain image classification. 2024 Second International Conference on Emerging Trends in Information Technology and Engineering (ICETITE) (pp. 1-8). IEEE.","DOI":"10.1109\/ic-ETITE58242.2024.10493757"},{"issue":"14","key":"10.1016\/j.eswa.2026.132297_b0095","doi-asserted-by":"crossref","first-page":"23956","DOI":"10.1364\/OE.522932","article-title":"Water pollution classification and detection by hyperspectral imaging","volume":"32","author":"Leung","year":"2024","journal-title":"Optics Express"},{"key":"10.1016\/j.eswa.2026.132297_b0100","article-title":"HSIAO framework in feature selection for hyperspectral remote sensing images based on Jeffries-Matusita distance","author":"Li","year":"2025","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"key":"10.1016\/j.eswa.2026.132297_b0105","article-title":"An information entropy feature preservation-based band selection and noise reduction method for hyperspectral image classification","author":"Li","year":"2026","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"issue":"1","key":"10.1016\/j.eswa.2026.132297_b0110","doi-asserted-by":"crossref","first-page":"9123","DOI":"10.1038\/s41598-024-59553-y","article-title":"From sensor fusion to knowledge distillation in collaborative LIBS and hyperspectral imaging for mineral identification","volume":"14","author":"Lopes","year":"2024","journal-title":"Scientific Reports"},{"issue":"3","key":"10.1016\/j.eswa.2026.132297_b0115","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1016\/0098-3004(93)90090-R","article-title":"Principal components analysis (PCA)","volume":"19","author":"Ma\u0107kiewicz","year":"1993","journal-title":"Computers & Geosciences"},{"issue":"1","key":"10.1016\/j.eswa.2026.132297_b0120","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1016\/j.biosystemseng.2008.05.017","article-title":"Feasibility of near-infrared hyperspectral imaging to differentiate Canadian wheat classes","volume":"101","author":"Mahesh","year":"2008","journal-title":"Biosystems Engineering"},{"key":"10.1016\/j.eswa.2026.132297_b0125","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1016\/j.advengsoft.2016.01.008","article-title":"The whale optimization algorithm","volume":"95","author":"Mirjalili","year":"2016","journal-title":"Advances in Engineering Software"},{"key":"10.1016\/j.eswa.2026.132297_b0130","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.advengsoft.2013.12.007","article-title":"Grey wolf optimizer","volume":"69","author":"Mirjalili","year":"2014","journal-title":"Advances in Engineering Software"},{"key":"10.1016\/j.eswa.2026.132297_b0135","doi-asserted-by":"crossref","first-page":"56870","DOI":"10.1109\/ACCESS.2018.2872801","article-title":"Ensemble feature selection for plant phenotyping: A journey from hyperspectral to multispectral imaging","volume":"6","author":"Moghimi","year":"2018","journal-title":"IEEE Access"},{"key":"10.1016\/j.eswa.2026.132297_b0140","doi-asserted-by":"crossref","DOI":"10.1016\/j.compbiomed.2022.105858","article-title":"Enhanced whale optimization algorithm for medical feature selection: A COVID-19 case study","volume":"148","author":"Nadimi-Shahraki","year":"2022","journal-title":"Computers in Biology and Medicine"},{"key":"10.1016\/j.eswa.2026.132297_b0145","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2024.111880","article-title":"The hiking optimization algorithm: A novel human-based metaheuristic approach","volume":"296","author":"Oladejo","year":"2024","journal-title":"Knowledge-based systems"},{"key":"10.1016\/j.eswa.2026.132297_b0150","doi-asserted-by":"crossref","first-page":"1952","DOI":"10.1109\/TIP.2023.3258739","article-title":"Multi-objective unsupervised band selection method for hyperspectral images classification","volume":"32","author":"Ou","year":"2023","journal-title":"IEEE Transactions on Image Processing"},{"key":"10.1016\/j.eswa.2026.132297_b0155","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2020.113400","article-title":"Euclidean distance based feature ranking and subset selection for bearing fault diagnosis","volume":"154","author":"Patel","year":"2020","journal-title":"Expert Systems with Applications"},{"issue":"8","key":"10.1016\/j.eswa.2026.132297_b0160","doi-asserted-by":"crossref","first-page":"1226","DOI":"10.1109\/TPAMI.2005.159","article-title":"Feature selection based on mutual information criteria of max-dependency, max-relevance, and min-redundancy","volume":"27","author":"Peng","year":"2005","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"10.1016\/j.eswa.2026.132297_b0165","doi-asserted-by":"crossref","first-page":"396","DOI":"10.1016\/j.procs.2016.07.226","article-title":"Dimensionality reduction using band selection technique for kernel based hyperspectral image classification","volume":"93","author":"Reshma","year":"2016","journal-title":"Procedia Computer Science"},{"issue":"4","key":"10.1016\/j.eswa.2026.132297_b0170","doi-asserted-by":"crossref","first-page":"667","DOI":"10.1038\/s41433-024-03135-9","article-title":"Hyperspectral retinal imaging biomarkers of ocular and systemic diseases","volume":"39","author":"Saeed","year":"2025","journal-title":"Eye"},{"key":"10.1016\/j.eswa.2026.132297_b0175","doi-asserted-by":"crossref","unstructured":"Sch\u00f6lkopf, B., Smola, A., & M\u00fcller, K.-R. (1997). Kernel principal component analysis. International conference on artificial neural networks (pp. 583-588). Springer.","DOI":"10.1007\/BFb0020217"},{"key":"10.1016\/j.eswa.2026.132297_b0180","first-page":"1","article-title":"A multihop graph rectify attention and spectral overlap grouping convolutional fusion network for hyperspectral image classification","volume":"62","author":"Shi","year":"2024","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"issue":"4","key":"10.1016\/j.eswa.2026.132297_b0185","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1023\/A:1008202821328","article-title":"Differential evolution\u2013a simple and efficient heuristic for global optimization over continuous spaces","volume":"11","author":"Storn","year":"1997","journal-title":"Journal of Global Optimization"},{"key":"10.1016\/j.eswa.2026.132297_b0190","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1016\/j.neucom.2023.02.010","article-title":"RIME: A physics-based optimization","volume":"532","author":"Su","year":"2023","journal-title":"Neurocomputing"},{"issue":"9","key":"10.1016\/j.eswa.2026.132297_b0195","doi-asserted-by":"crossref","first-page":"3665","DOI":"10.1109\/JSTARS.2019.2922201","article-title":"Hyperspectral band selection using weighted kernel regularization","volume":"12","author":"Sun","year":"2019","journal-title":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"},{"issue":"22","key":"10.1016\/j.eswa.2026.132297_b0200","doi-asserted-by":"crossref","first-page":"5679","DOI":"10.3390\/rs14225679","article-title":"Multiple band prioritization criteria-based band selection for hyperspectral imagery","volume":"14","author":"Sun","year":"2022","journal-title":"Remote Sensing"},{"key":"10.1016\/j.eswa.2026.132297_b0205","article-title":"A hyperspectral feature selection method for soil organic matter estimation based on an improved weighted marine predators algorithm","author":"Tan","year":"2024","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"issue":"6","key":"10.1016\/j.eswa.2026.132297_b0210","doi-asserted-by":"crossref","first-page":"2918","DOI":"10.1109\/TIP.2017.2687128","article-title":"Feature selection based on high dimensional model representation for hyperspectral images","volume":"26","author":"Ta\u015fk\u0131n","year":"2017","journal-title":"IEEE Transactions on Image Processing"},{"key":"10.1016\/j.eswa.2026.132297_b0215","doi-asserted-by":"crossref","first-page":"8326","DOI":"10.1109\/JSTARS.2021.3104153","article-title":"Feature extraction using multidimensional spectral regression whitening for hyperspectral image classification","volume":"14","author":"Tu","year":"2021","journal-title":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"},{"key":"10.1016\/j.eswa.2026.132297_b0220","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2020.106642","article-title":"Evolutionary biogeography-based whale optimization methods with communication structure: Towards measuring the balance","volume":"212","author":"Tu","year":"2021","journal-title":"Knowledge-based systems"},{"issue":"12","key":"10.1016\/j.eswa.2026.132297_b0225","doi-asserted-by":"crossref","first-page":"4940","DOI":"10.1109\/JSTARS.2019.2941454","article-title":"Hyperspectral band selection via adaptive subspace partition strategy","volume":"12","author":"Wang","year":"2019","journal-title":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"},{"issue":"6","key":"10.1016\/j.eswa.2026.132297_b0230","doi-asserted-by":"crossref","first-page":"5028","DOI":"10.1109\/TGRS.2020.3011002","article-title":"A fast neighborhood grouping method for hyperspectral band selection","volume":"59","author":"Wang","year":"2020","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"key":"10.1016\/j.eswa.2026.132297_b0235","article-title":"HSCRN: A hyperspectral image classification network based on dynamic context and feature refinement","volume":"192","author":"Wang","year":"2025","journal-title":"Optics & Laser Technology"},{"key":"10.1016\/j.eswa.2026.132297_b0240","first-page":"1","article-title":"A hybrid gray wolf optimizer for hyperspectral image band selection","volume":"60","author":"Wang","year":"2022","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"key":"10.1016\/j.eswa.2026.132297_b0245","doi-asserted-by":"crossref","first-page":"6414","DOI":"10.1109\/JSTARS.2024.3372138","article-title":"An evaluation of convolutional neural networks for lithological mapping based on hyperspectral images","volume":"17","author":"Wang","year":"2024","journal-title":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"},{"issue":"7","key":"10.1016\/j.eswa.2026.132297_b0250","doi-asserted-by":"crossref","first-page":"2880","DOI":"10.1109\/TGRS.2010.2041784","article-title":"Sensitivity of support vector machines to random feature selection in classification of hyperspectral data","volume":"48","author":"Waske","year":"2010","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"key":"10.1016\/j.eswa.2026.132297_b0255","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2022.117428","article-title":"A ranking-based adaptive cuckoo search algorithm for unconstrained optimization","volume":"204","author":"Wei","year":"2022","journal-title":"Expert Systems with Applications"},{"key":"10.1016\/j.eswa.2026.132297_b0260","doi-asserted-by":"crossref","unstructured":"Wold, S., Martens, H., & Wold, H. (2006). The multivariate calibration problem in chemistry solved by the PLS method. Matrix Pencils: Proceedings of a Conference Held at Pite Havsbad, Sweden, March 22\u201324, 1982 (pp. 286-293). Springer.","DOI":"10.1007\/BFb0062108"},{"issue":"10","key":"10.1016\/j.eswa.2026.132297_b0265","doi-asserted-by":"crossref","first-page":"11068","DOI":"10.1109\/TCYB.2021.3106485","article-title":"Multiview PCA: A methodology of feature extraction and dimension reduction for high-order data","volume":"52","author":"Xia","year":"2021","journal-title":"IEEE Transactions on Cybernetics"},{"key":"10.1016\/j.eswa.2026.132297_b0270","doi-asserted-by":"crossref","DOI":"10.1016\/j.jhazmat.2024.136724","article-title":"A green and efficient method for detecting nicosulfuron residues in field maize using hyperspectral imaging and deep learning","volume":"484","author":"Xiao","year":"2025","journal-title":"Journal of Hazardous Materials"},{"issue":"17","key":"10.1016\/j.eswa.2026.132297_b0275","doi-asserted-by":"crossref","first-page":"10019","DOI":"10.1021\/acs.jafc.4c11492","article-title":"Hyperspectral imaging and deep learning for quality and safety inspection of fruits and vegetables: A review","volume":"73","author":"Yang","year":"2025","journal-title":"Journal of Agricultural and Food Chemistry"},{"key":"10.1016\/j.eswa.2026.132297_b0280","series-title":"Cuckoo search via L\u00e9vy flights. 2009 World congress on nature & biologically inspired computing (NaBIC)","first-page":"210","author":"Yang","year":"2009"},{"key":"10.1016\/j.eswa.2026.132297_b0285","doi-asserted-by":"crossref","DOI":"10.1016\/j.compbiomed.2022.105510","article-title":"An optimized machine learning framework for predicting intradialytic hypotension using indexes of chronic kidney disease-mineral and bone disorders","volume":"145","author":"Yang","year":"2022","journal-title":"Computers in Biology and Medicine"},{"key":"10.1016\/j.eswa.2026.132297_b0290","doi-asserted-by":"crossref","DOI":"10.1016\/j.displa.2024.102740","article-title":"Artemisinin optimization based on malaria therapy: Algorithm and applications to medical image segmentation","volume":"84","author":"Yuan","year":"2024","journal-title":"Displays"},{"issue":"12","key":"10.1016\/j.eswa.2026.132297_b0295","doi-asserted-by":"crossref","first-page":"4172","DOI":"10.1109\/TGRS.2007.905311","article-title":"Dimensionality reduction based on clonal selection for hyperspectral imagery","volume":"45","author":"Zhang","year":"2007","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"key":"10.1016\/j.eswa.2026.132297_b0300","doi-asserted-by":"crossref","DOI":"10.1016\/j.swevo.2024.101614","article-title":"Multiobjective band selection approach via an adaptive particle swarm optimizer for remote sensing hyperspectral images","volume":"89","author":"Zhang","year":"2024","journal-title":"Swarm and Evolutionary Computation"},{"key":"10.1016\/j.eswa.2026.132297_b0305","article-title":"A hyperspectral classification method based on deep learning and dimension reduction for ground environmental monitoring","author":"Zhe","year":"2025","journal-title":"IEEE Access"},{"key":"10.1016\/j.eswa.2026.132297_b0310","first-page":"1","article-title":"From intra-distinctiveness to inter-invariance: A cycle-resemblance few-shot transformation network for cross-domain hyperspectral image classification","volume":"63","author":"Zhu","year":"2024","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"}],"container-title":["Expert Systems with Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0957417426012108?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0957417426012108?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,6,13]],"date-time":"2026-06-13T00:08:49Z","timestamp":1781309329000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0957417426012108"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8]]},"references-count":62,"alternative-id":["S0957417426012108"],"URL":"https:\/\/doi.org\/10.1016\/j.eswa.2026.132297","relation":{},"ISSN":["0957-4174"],"issn-type":[{"value":"0957-4174","type":"print"}],"subject":[],"published":{"date-parts":[[2026,8]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"DIGWO_BS: a hyperspectral band selection optimization framework for preserving spectral structure","name":"articletitle","label":"Article Title"},{"value":"Expert Systems with Applications","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.eswa.2026.132297","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"132297"}}