{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,9]],"date-time":"2026-05-09T00:13:20Z","timestamp":1778285600004,"version":"3.51.4"},"reference-count":62,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100007129","name":"Shandong Province Natural Science Foundation","doi-asserted-by":"publisher","award":["ZR2024QE414"],"award-info":[{"award-number":["ZR2024QE414"]}],"id":[{"id":"10.13039\/501100007129","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52525905"],"award-info":[{"award-number":["52525905"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52379103"],"award-info":[{"award-number":["52379103"]}],"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":[[2026,7]]},"DOI":"10.1016\/j.engappai.2026.114653","type":"journal-article","created":{"date-parts":[[2026,4,6]],"date-time":"2026-04-06T12:36:10Z","timestamp":1775478970000},"page":"114653","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"P1","title":["A new mineral quantification method via experiment-enhanced transfer learning of linear mixed mid-infrared spectra data"],"prefix":"10.1016","volume":"176","author":[{"given":"Tao","family":"Han","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tengfei","family":"Yu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peng","family":"Lin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wen","family":"Ma","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6578-7583","authenticated-orcid":false,"given":"Zhenhao","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"key":"10.1016\/j.engappai.2026.114653_bib1","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1109\/LGRS.2008.2006005","article-title":"Longwave thermal infrared spectral variability in individual rocks","volume":"6","author":"Balick","year":"2009","journal-title":"Ieee Geosci Remote S"},{"key":"10.1016\/j.engappai.2026.114653_bib2","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2023.107680","article-title":"Hybrid features extraction for the online mineral grades determination in the flotation froth using Deep Learning","volume":"129","author":"Bendaouia","year":"2024","journal-title":"Eng Appl Artif Intel"},{"key":"10.1016\/j.engappai.2026.114653_bib3","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/S1386-1425(99)00134-1","article-title":"Ochre-differentiation through micro-Raman and micro-FTIR spectroscopies: application on wall paintings at Meteora and Mount Athos, Greece","volume":"56","author":"Bikiaris","year":"2000","journal-title":"Spectrochim. Acta"},{"key":"10.1016\/j.engappai.2026.114653_bib4","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1180\/claymin.2008.043.1.03","article-title":"Reflectance and emission spectroscopy study of four groups of phyllosilicates: smectites, kaolinite-serpentines, chlorites and micas","volume":"43","author":"Bishop","year":"2008","journal-title":"Clay Miner."},{"key":"10.1016\/j.engappai.2026.114653_bib5","first-page":"25","article-title":"Semi\u2010Quantification of the calcium carbonate in marine sediments by visible and near\u2010infrared diffuse reflectance spectroscopy","volume":"G3","author":"Cao","year":"2024","journal-title":"G-cubed"},{"key":"10.1016\/j.engappai.2026.114653_bib6","article-title":"Learning imbalanced datasets with label-distribution-aware Margin loss","volume":"32","author":"Cao","year":"2019","journal-title":"Adv Neur"},{"key":"10.1016\/j.engappai.2026.114653_bib7","doi-asserted-by":"crossref","DOI":"10.1029\/2000JE001462","article-title":"Midinfrared spectral features of rocks and their powders - art. no. 5017","volume":"107","author":"Cooper","year":"2002","journal-title":"J Geophys Res-Planet"},{"key":"10.1016\/j.engappai.2026.114653_bib8","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2025.111784","article-title":"A strongly supervised hyperspectral unmixing framework for precise mineral composition and coal ash content estimation","volume":"159","author":"Cui","year":"2025","journal-title":"Eng Appl Artif Intel"},{"key":"10.1016\/j.engappai.2026.114653_bib10","doi-asserted-by":"crossref","first-page":"230","DOI":"10.1109\/TGRS.1987.289822","article-title":"Mid-Infrared remote sensing systems and their application to lithologic mapping","volume":"25","author":"Eberhardt","year":"1987","journal-title":"IEEE Transactions on Geoscience & Remote Sensing GE-"},{"key":"10.1016\/j.engappai.2026.114653_bib11","series-title":"The Infrared Spectra of Minerals","article-title":"The layer silicates","author":"Farmer","year":"1974"},{"key":"10.1016\/j.engappai.2026.114653_bib12","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/08120099.2025.2464839","article-title":"Joint unmixing of SWIR and TIR reflectance spectra for mineral composition","volume":"73","author":"Green","year":"2025","journal-title":"Aust. J. Earth Sci."},{"key":"10.1016\/j.engappai.2026.114653_bib13","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1016\/j.enggeo.2017.03.012","article-title":"Multi-scale analysis of the mechanical improvement induced by lime addition on a pyroclastic soil","volume":"221","author":"Guidobaldi","year":"2017","journal-title":"Eng Geol"},{"key":"10.1016\/j.engappai.2026.114653_bib14","doi-asserted-by":"crossref","DOI":"10.1016\/j.geoderma.2021.115071","article-title":"Prediction of various soil properties for a national spatial dataset of Scottish soils based on four different chemometric approaches: a comparison of near infrared and mid-infrared spectroscopy","volume":"396","author":"Haghi","year":"2021","journal-title":"Geoderma"},{"key":"10.1016\/j.engappai.2026.114653_bib15","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1016\/0924-2031(93)87057-Z","article-title":"Vibrational spectroscopy of the amorphous silicates","volume":"5","author":"Handke","year":"1993","journal-title":"Vib. Spectrosc."},{"key":"10.1016\/j.engappai.2026.114653_bib16","doi-asserted-by":"crossref","DOI":"10.1029\/2011GC004004","article-title":"Thermal infrared spectroscopy and partial least squares regression to determine mineral modes of granitoid rocks","volume":"13","author":"Hecker","year":"2012","journal-title":"Geochem Geophy Geosy"},{"key":"10.1016\/j.engappai.2026.114653_bib17","doi-asserted-by":"crossref","first-page":"1545","DOI":"10.1109\/TGRS.2015.2482386","article-title":"Noise simulation and correction in synthetic airborne TIR data for mineral quantification","volume":"54","author":"Hecker","year":"2016","journal-title":"Ieee T Geosci Remote"},{"key":"10.1016\/j.engappai.2026.114653_bib18","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1016\/j.earscirev.2010.07.005","article-title":"Thermal infrared spectroscopy on feldspars - successes, limitations and their implications for remote sensing","volume":"103","author":"Hecker","year":"2010","journal-title":"Earth Sci. Rev."},{"key":"10.1016\/j.engappai.2026.114653_bib19","series-title":"Gaussian Error Linear Units (Gelus)","author":"Hendrycks","year":"2016"},{"key":"10.1016\/j.engappai.2026.114653_bib20","first-page":"939","article-title":"Short wavelength infrared (SWIR) spectral analysis of hydrothermal alteration zones associated with base metal sulfide deposits at Rosebery and Western Tharsis, Tasmania, and Highway-Reward, Queensland","volume":"96","author":"Herrmann","year":"2001","journal-title":"Econ Geol Bull Soc"},{"key":"10.1016\/j.engappai.2026.114653_bib21","doi-asserted-by":"crossref","DOI":"10.1016\/j.geoderma.2019.113900","article-title":"In situ and laboratory soil spectroscopy with portable visible-to-near-infrared and mid-infrared instruments for the assessment of organic carbon in soils","volume":"355","author":"Hutengs","year":"2019","journal-title":"Geoderma"},{"key":"10.1016\/j.engappai.2026.114653_bib22","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1524\/zkri.1971.134.3-4.213","article-title":"The force field of K feldspar","volume":"134","author":"Iiishi","year":"1971","journal-title":"Z. Kristallogr. Cryst. Mater."},{"key":"10.1016\/j.engappai.2026.114653_bib23","doi-asserted-by":"crossref","first-page":"183","DOI":"10.3319\/TAO.2007.18.2.183(TCDP)","article-title":"Structural, mineralogical, and geochemical characterization of the Chelungpu thrust fault, Taiwan","volume":"18","author":"Isaacs","year":"2007","journal-title":"Terr. Atmos. Ocean Sci."},{"key":"10.1016\/j.engappai.2026.114653_bib24","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1016\/S0016-7061(02)00175-1","article-title":"Review of XRD-based quantitative analyses of clay minerals in soils: the suitability of mineral intensity factors","volume":"109","author":"Kahle","year":"2002","journal-title":"Geoderma"},{"key":"10.1016\/j.engappai.2026.114653_bib25","doi-asserted-by":"crossref","first-page":"2297","DOI":"10.1016\/j.rse.2010.05.006","article-title":"Mineral mapping in the Pyramid Lake basin: hydrothermal alteration, chemical precipitates and geothermal energy potential","volume":"114","author":"Kratt","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"10.1016\/j.engappai.2026.114653_bib26","doi-asserted-by":"crossref","first-page":"25581","DOI":"10.1029\/97JE02046","article-title":"Thermal infrared emission spectroscopy of anhydrous carbonates","volume":"102","author":"Lane","year":"1997","journal-title":"J Geophys Res-Planet"},{"key":"10.1016\/j.engappai.2026.114653_bib27","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/j.pss.2018.04.010","article-title":"Raman, Mid-IR, and NIR spectroscopic study of calcium sulfates and mapping gypsum abundances in Columbus crater, Mars","volume":"163","author":"Liu","year":"2018","journal-title":"Planet. Space Sci."},{"key":"10.1016\/j.engappai.2026.114653_bib28","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1046\/j.1365-3121.2000.00264.x","article-title":"Determination of metamorphic grade in siliceous muscovite-bearing rocks in Madagascar using reflectance spectroscopy","volume":"12","author":"Longhi","year":"2000","journal-title":"Terra Nova"},{"key":"10.1016\/j.engappai.2026.114653_bib29","doi-asserted-by":"crossref","DOI":"10.1016\/j.catena.2024.108115","article-title":"Application of mid-infrared (MIR) spectroscopy to identify and quantify minerals in New Zealand soils","volume":"242","author":"Ma","year":"2024","journal-title":"Catena"},{"key":"10.1016\/j.engappai.2026.114653_bib30","doi-asserted-by":"crossref","DOI":"10.1016\/j.mineng.2025.109803","article-title":"A new mineral quantification method via global feature fusion of plane-polarized and cross-polarized light images: mqm-p\/xpl","volume":"235","author":"Ma","year":"2026","journal-title":"Miner. Eng."},{"key":"10.1016\/j.engappai.2026.114653_bib31","doi-asserted-by":"crossref","DOI":"10.1016\/j.cageo.2025.105987","article-title":"An innovative adaptive mineral segmentation method via augmentation and fusion of single and orthogonal polarized images: ams-p\/xpl","volume":"204","author":"Ma","year":"2025","journal-title":"Comput Geosci-Uk"},{"key":"10.1016\/j.engappai.2026.114653_bib32","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1016\/j.vibspec.2008.08.001","article-title":"Near-infrared spectroscopy: a powerful tool in studies of acid-treated clay minerals","volume":"49","author":"Madejov\u00e1","year":"2009","journal-title":"Vib. Spectrosc."},{"key":"10.1016\/j.engappai.2026.114653_bib33","doi-asserted-by":"crossref","first-page":"413","DOI":"10.1016\/j.molstruc.2009.01.001","article-title":"Minerals from Macedonia. XXIV. Spectra-structure characterization of tectosilicates","volume":"924","author":"Makreski","year":"2009","journal-title":"J. Mol. Struct."},{"key":"10.1016\/j.engappai.2026.114653_bib34","doi-asserted-by":"crossref","DOI":"10.1029\/2009JE003495","article-title":"Distribution and variation of plagioclase compositions on Mars","volume":"115","author":"Milam","year":"2010","journal-title":"J Geophys Res-Planet"},{"key":"10.1016\/j.engappai.2026.114653_bib35","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1016\/j.geoderma.2019.06.016","article-title":"Convolutional neural network for simultaneous prediction of several soil properties using visible\/near-infrared, mid-infrared, and their combined spectra","volume":"352","author":"Ng","year":"2019","journal-title":"Geoderma"},{"key":"10.1016\/j.engappai.2026.114653_bib36","doi-asserted-by":"crossref","DOI":"10.1016\/j.petrol.2022.110912","article-title":"Integrated reflection-FTIR and multivariate partial least squares approach for rapid and accurate assessment of total organic carbon concentration in shale","volume":"217","author":"Oye","year":"2022","journal-title":"J. Petrol. Sci. Eng."},{"key":"10.1016\/j.engappai.2026.114653_bib37","doi-asserted-by":"crossref","first-page":"886","DOI":"10.1109\/LGRS.2020.2989796","article-title":"Hapke data augmentation for deep learning-based hyperspectral data analysis with limited samples","volume":"18","author":"Qin","year":"2021","journal-title":"Ieee Geosci Remote S"},{"key":"10.1016\/j.engappai.2026.114653_bib38","doi-asserted-by":"crossref","first-page":"577","DOI":"10.1029\/97JB02784","article-title":"Mineral abundance determination: quantitative deconvolution of thermal emission spectra","volume":"103","author":"Ramsey","year":"1998","journal-title":"J. Geophys. Res. Solid Earth"},{"key":"10.1016\/j.engappai.2026.114653_bib39","doi-asserted-by":"crossref","first-page":"1803","DOI":"10.1007\/s10994-020-05900-9","article-title":"Imbalanced regression and extreme value prediction","volume":"109","author":"Ribeiro","year":"2020","journal-title":"Mach. Learn."},{"issue":"1","key":"10.1016\/j.engappai.2026.114653_bib40","first-page":"1","article-title":"The mid-infrared reflectance of mineral mixtures (7\u201314 \u03bcm)","volume":"45","author":"Salisbury","year":"1993","journal-title":"Remote Sens. Environ."},{"key":"10.1016\/j.engappai.2026.114653_bib41","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1016\/j.aca.2004.10.086","article-title":"Ensemble methods and data augmentation by noise addition applied to the analysis of spectroscopic data","volume":"533","author":"S\u00e1iz-Abajo","year":"2005","journal-title":"Anal. Chim. Acta"},{"key":"10.1016\/j.engappai.2026.114653_bib42","doi-asserted-by":"crossref","DOI":"10.3389\/fbioe.2024.1228846","article-title":"Generative data augmentation and automated optimization of convolutional neural networks for process monitoring","volume":"12","author":"Schiemer","year":"2024","journal-title":"Front Bioeng Biotech"},{"key":"10.1016\/j.engappai.2026.114653_bib43","doi-asserted-by":"crossref","first-page":"6007","DOI":"10.1109\/JSEN.2025.3650493","article-title":"An improved variational autoencoder and graph attention network method for wear prediction of aerospace self-lubricating bearing using acoustic emission signal","volume":"26","author":"Shen","year":"2026","journal-title":"Ieee Sens J"},{"key":"10.1016\/j.engappai.2026.114653_bib44","doi-asserted-by":"crossref","first-page":"190","DOI":"10.1016\/j.isprsjprs.2022.04.009","article-title":"Deep transfer learning of global spectra for local soil carbon monitoring","volume":"188","author":"Shen","year":"2022","journal-title":"Isprs J Photogramm"},{"key":"10.1016\/j.engappai.2026.114653_bib45","doi-asserted-by":"crossref","first-page":"6945","DOI":"10.1080\/01431161.2021.1948625","article-title":"Readily dispersible clay in soils from different Brazilian regions by visible, near, and mid-infrared spectral data","volume":"42","author":"Silva","year":"2021","journal-title":"Int. J. Rem. Sens."},{"key":"10.1016\/j.engappai.2026.114653_bib46","first-page":"116","article-title":"Vibrational spectroscopic study of muscovite and biotite layered phyllosilicates","volume":"54","author":"Singha","year":"2016","journal-title":"Indian J Pure Ap Phy"},{"key":"10.1016\/j.engappai.2026.114653_bib47","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2025.113082","article-title":"Cross-modal feature fusion and distillation for enhanced quantification accuracy in laser-induced breakdown spectroscopy and near-infrared spectroscopy","volume":"163","author":"Song","year":"2026","journal-title":"Eng Appl Artif Intel"},{"key":"10.1016\/j.engappai.2026.114653_bib48","doi-asserted-by":"crossref","DOI":"10.1016\/j.infrared.2023.104559","article-title":"1D-inception-resnet for NIR quantitative analysis and its transferability between different spectrometers","volume":"129","author":"Tan","year":"2023","journal-title":"Infrared Phys Techn"},{"key":"10.1016\/j.engappai.2026.114653_bib49","doi-asserted-by":"crossref","DOI":"10.1016\/j.microc.2024.111815","article-title":"Using convolutional neural network combined with multi-scale channel attention module to predict soil properties from visible and near-infrared spectral data","volume":"207","author":"Tang","year":"2024","journal-title":"Microchem. J."},{"key":"10.1016\/j.engappai.2026.114653_bib50","doi-asserted-by":"crossref","first-page":"1765","DOI":"10.1109\/LGRS.2018.2856406","article-title":"Multiharmonic postnonlinear mixing model for hyperspectral nonlinear unmixing","volume":"15","author":"Tang","year":"2018","journal-title":"Ieee Geosci Remote S"},{"key":"10.1016\/j.engappai.2026.114653_bib51","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2025.110527","article-title":"Identification of Martian minerals based on multiscale spatial-spectral fusion network","volume":"149","author":"Wang","year":"2025","journal-title":"Eng Appl Artif Intel"},{"key":"10.1016\/j.engappai.2026.114653_bib52","doi-asserted-by":"crossref","first-page":"36513","DOI":"10.1109\/JSEN.2025.3597796","article-title":"MTCAT: a modern temporal convolution and enhanced attention transformer model for remaining useful life prediction of aerospace self-lubricating bearings","volume":"25","author":"Wang","year":"2025","journal-title":"Ieee Sens J"},{"key":"10.1016\/j.engappai.2026.114653_bib53","first-page":"1","article-title":"Four typical variation patterns of mid-infrared spectra of the mafic mineral anomalies for fault zone identification. Tunn Undergr Sp","volume":"162","author":"Xu","year":"2025","journal-title":"Tech"},{"key":"10.1016\/j.engappai.2026.114653_bib54","first-page":"150","article-title":"Adverse geology identification through mineral Anomaly analysis during tunneling: methodology and case Study","volume":"27","author":"Xu","year":"2023","journal-title":"Engineering-Prc"},{"key":"10.1016\/j.engappai.2026.114653_bib55","doi-asserted-by":"crossref","DOI":"10.1016\/j.enggeo.2023.107279","article-title":"Anomalous patterns of clay minerals in fault zones","volume":"325","author":"Xu","year":"2023","journal-title":"Eng Geol"},{"key":"10.1016\/j.engappai.2026.114653_bib56","doi-asserted-by":"crossref","DOI":"10.1016\/j.talanta.2025.128006","article-title":"Quantitative analysis of plastic blends based on virtual mid-infrared spectroscopy combined with chemometric methods","volume":"292","author":"Yang","year":"2025","journal-title":"Talanta"},{"key":"10.1016\/j.engappai.2026.114653_bib57","doi-asserted-by":"crossref","first-page":"581","DOI":"10.1016\/j.clay.2011.05.007","article-title":"Spectral characteristics of clay minerals in the 2.5-14 \u03bcm wavelength region","volume":"53","author":"Yitagesu","year":"2011","journal-title":"Appl. Clay Sci."},{"key":"10.1016\/j.engappai.2026.114653_bib58","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1016\/j.gexplo.2012.02.002","article-title":"Geochemical mineralization probability index (GMPI): a new approach to generate enhanced stream sediment geochemical evidential map for increasing probability of success in mineral potential mapping","volume":"115","author":"Yousefi","year":"2012","journal-title":"J. Geochem. Explor."},{"key":"10.1016\/j.engappai.2026.114653_bib59","article-title":"Four typical variation patterns of mid-infrared Spectra of the felsic mineral anomalies for fault Zone identification","volume":"63","author":"Yu","year":"2025","journal-title":"Ieee T Geosci Remote"},{"key":"10.1016\/j.engappai.2026.114653_bib60","doi-asserted-by":"crossref","first-page":"110823","DOI":"10.1016\/j.foodcont.2024.110823","article-title":"A 1D-inception-ResNet based global detection model for thin-skinned multifruit spectral quantitative analysis","volume":"167","author":"Yu","year":"2025","journal-title":"Food Control"},{"key":"10.1016\/j.engappai.2026.114653_bib61","doi-asserted-by":"crossref","DOI":"10.1016\/j.geoderma.2025.117207","article-title":"Deep learning of the particulate and mineral-associated organic carbon fractions using a compositional transform and mid-infrared spectroscopy","volume":"455","author":"Zhang","year":"2025","journal-title":"Geoderma"},{"key":"10.1016\/j.engappai.2026.114653_bib62","doi-asserted-by":"crossref","DOI":"10.1016\/j.rse.2021.112724","article-title":"Transfer-learning-based approach for leaf chlorophyll content estimation of winter wheat from hyperspectral data","volume":"267","author":"Zhang","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"10.1016\/j.engappai.2026.114653_bib63","doi-asserted-by":"crossref","first-page":"357","DOI":"10.1016\/j.jmsy.2025.09.015","article-title":"Flexible pallet automation system scheduling with limited fixture-pallets and material-pallets: a case study from an engine manufacturing enterprise","volume":"83","author":"Zhou","year":"2025","journal-title":"J. Manuf. Syst."}],"container-title":["Engineering Applications of Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0952197626009358?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0952197626009358?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T23:34:31Z","timestamp":1778283271000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0952197626009358"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7]]},"references-count":62,"alternative-id":["S0952197626009358"],"URL":"https:\/\/doi.org\/10.1016\/j.engappai.2026.114653","relation":{},"ISSN":["0952-1976"],"issn-type":[{"value":"0952-1976","type":"print"}],"subject":[],"published":{"date-parts":[[2026,7]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A new mineral quantification method via experiment-enhanced transfer learning of linear mixed mid-infrared spectra data","name":"articletitle","label":"Article Title"},{"value":"Engineering Applications of Artificial Intelligence","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.engappai.2026.114653","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":"114653"}}