{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,9]],"date-time":"2026-05-09T00:13:03Z","timestamp":1778285583857,"version":"3.51.4"},"reference-count":51,"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\/100016807","name":"Natural Science Foundation of Shenyang Municipality","doi-asserted-by":"publisher","award":["23-503-6-01"],"award-info":[{"award-number":["23-503-6-01"]}],"id":[{"id":"10.13039\/100016807","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100007620","name":"Department of Education of Liaoning Province","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100007620","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.2026.114622","type":"journal-article","created":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T19:42:04Z","timestamp":1775245324000},"page":"114622","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"P1","title":["High-fidelity imaging of laser-directed energy deposition via a dual-stage strategy of exposure optimization and adaptive enhancement"],"prefix":"10.1016","volume":"176","author":[{"given":"Jiazhen","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7278-7971","authenticated-orcid":false,"given":"Xingyu","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ao","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shun","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qingze","family":"Tan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weijun","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhiqiang","family":"Tian","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"key":"10.1016\/j.engappai.2026.114622_bib1","series-title":"Fundamentals of Heat and Mass Transfer","author":"Bergman","year":"2011"},{"key":"10.1016\/j.engappai.2026.114622_bib2","article-title":"Learning a deep single image contrast enhancer from multi-exposure images","author":"Cai","year":"2018","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.engappai.2026.114622_bib3","doi-asserted-by":"crossref","first-page":"695","DOI":"10.1016\/j.jmapro.2022.02.058","article-title":"Real-time identification of molten pool and keyhole using a deep learning-based semantic segmentation approach in penetration status monitoring","volume":"76","author":"Cai","year":"2022","journal-title":"J. Manuf. Process."},{"key":"10.1016\/j.engappai.2026.114622_bib4","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1016\/j.jmsy.2023.07.018","article-title":"A review of in-situ monitoring and process control system in metal-based laser additive manufacturing","volume":"70","author":"Cai","year":"2023","journal-title":"J. Manuf. Syst."},{"key":"10.1016\/j.engappai.2026.114622_bib5","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1016\/j.rcim.2023.102581","article-title":"Multisensor fusion-based digital twin for localized quality prediction in robotic laser-directed energy deposition","volume":"84","author":"Chen","year":"2023","journal-title":"Robot. Comput. Integrated Manuf."},{"key":"10.1016\/j.engappai.2026.114622_bib6","doi-asserted-by":"crossref","first-page":"527","DOI":"10.1016\/j.jmsy.2024.04.013","article-title":"In-situ process monitoring and adaptive quality enhancement in laser additive manufacturing: a critical review","volume":"74","author":"Chen","year":"2024","journal-title":"J. Manuf. Syst."},{"key":"10.1016\/j.engappai.2026.114622_bib7","doi-asserted-by":"crossref","first-page":"298","DOI":"10.1016\/j.cirpj.2021.06.015","article-title":"Process performance evaluation and classification via in-situ melt pool monitoring in directed energy deposition","volume":"35","author":"Ertay","year":"2021","journal-title":"Cirp J. Manufact. Sci. Technol."},{"key":"10.1016\/j.engappai.2026.114622_bib8","doi-asserted-by":"crossref","first-page":"347","DOI":"10.1016\/j.jmapro.2021.05.052","article-title":"In-situ capture of melt pool signature in selective laser melting using U-Net-based convolutional neural network","volume":"68","author":"Fang","year":"2021","journal-title":"J. Manuf. Process."},{"key":"10.1016\/j.engappai.2026.114622_bib9","doi-asserted-by":"crossref","first-page":"1917","DOI":"10.1007\/s11665-014-0958-z","article-title":"Metal additive manufacturing: a review","volume":"23","author":"Frazier","year":"2014","journal-title":"J. Mater. Eng. Perform."},{"key":"10.1016\/j.engappai.2026.114622_bib53","series-title":"Digital Image Processing","author":"Gonzalez","year":"2018"},{"issue":"1","key":"10.1016\/j.engappai.2026.114622_bib10","doi-asserted-by":"crossref","first-page":"477","DOI":"10.1109\/TCSVT.2024.3454160","article-title":"Perceptual information fidelity for quality estimation of industrial images","volume":"35","author":"Gu","year":"2024","journal-title":"IEEE Trans. Circ. Syst. Video Technol."},{"key":"10.1016\/j.engappai.2026.114622_bib11","doi-asserted-by":"crossref","first-page":"128","DOI":"10.1016\/j.jmapro.2023.12.004","article-title":"Review of in situ process monitoring for metal hybrid directed energy deposition","volume":"109","author":"Haley","year":"2024","journal-title":"J. Manuf. Process."},{"key":"10.1016\/j.engappai.2026.114622_bib12","first-page":"548","article-title":"Melt pool temperature and cooling rates in laser powder bed fusion","volume":"22","author":"Hooper","year":"2018","journal-title":"Addit. Manuf."},{"key":"10.1016\/j.engappai.2026.114622_bib13","first-page":"13","article-title":"Online melt pool depth estimation during directed energy deposition using coaxial infrared camera, laser line scanner, and artificial neural network","volume":"47","author":"Jeon","year":"2021","journal-title":"Addit. Manuf."},{"key":"10.1016\/j.engappai.2026.114622_bib14","doi-asserted-by":"crossref","first-page":"375","DOI":"10.1007\/s10845-018-1451-6","article-title":"A deep neural network for classification of melt-pool images in metal additive manufacturing","volume":"31","author":"Kwon","year":"2020","journal-title":"J. Intell. Manuf."},{"key":"10.1016\/j.engappai.2026.114622_bib15","doi-asserted-by":"crossref","first-page":"207","DOI":"10.1016\/j.jmapro.2019.05.013","article-title":"Real-time weld geometry prediction based on multi-information using neural network optimized by PCA and GA during thin-plate laser welding","volume":"43","author":"Lei","year":"2019","journal-title":"J. Manuf. Process."},{"key":"10.1016\/j.engappai.2026.114622_bib16","doi-asserted-by":"crossref","first-page":"4225","DOI":"10.1109\/TITS.2020.3042973","article-title":"Learning to enhance low-light image via zero-reference deep curve estimation","volume":"44","author":"Li","year":"2022","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.engappai.2026.114622_bib17","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"11976","article-title":"A convnet for the 2020s","author":"Liu","year":"2022"},{"key":"10.1016\/j.engappai.2026.114622_bib18","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1038\/s41467-020-14630-4","article-title":"High-resolution tomographic volumetric additive manufacturing","volume":"11","author":"Loterie","year":"2020","journal-title":"Nat. Commun."},{"key":"10.1016\/j.engappai.2026.114622_bib19","doi-asserted-by":"crossref","first-page":"336","DOI":"10.1016\/j.jmapro.2020.02.016","article-title":"In-situ optical emission spectroscopy of selective laser melting","volume":"53","author":"Lough","year":"2020","journal-title":"J. Manuf. Process."},{"key":"10.1016\/j.engappai.2026.114622_bib20","first-page":"10","article-title":"Quantitative prediction for weld reinforcement in arc welding additive manufacturing based on molten pool image and deep residual network","volume":"41","author":"Lu","year":"2021","journal-title":"Addit. Manuf."},{"key":"10.1016\/j.engappai.2026.114622_bib21","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1109\/TIM.2024.3432145","article-title":"Selective laser melting monitoring based on the plume and its motion features","volume":"73","author":"Mao","year":"2024","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"10.1016\/j.engappai.2026.114622_bib22","first-page":"19","article-title":"In-situ sensing, process monitoring and machine control in laser powder bed fusion: a review","volume":"45","author":"McCann","year":"2021","journal-title":"Addit. Manuf."},{"key":"10.1016\/j.engappai.2026.114622_bib23","doi-asserted-by":"crossref","first-page":"683","DOI":"10.1007\/s10845-021-01820-0","article-title":"In-situ monitoring laser based directed energy deposition process with deep convolutional neural network","volume":"34","author":"Mi","year":"2023","journal-title":"J. Intell. Manuf."},{"key":"10.1016\/j.engappai.2026.114622_bib24","article-title":"Two-color thermal imaging of the melt pool in powder-blown laser-directed energy deposition","volume":"78","author":"Myers","year":"2023","journal-title":"Addit. Manuf."},{"key":"10.1016\/j.engappai.2026.114622_bib25","doi-asserted-by":"crossref","DOI":"10.1016\/j.optlastec.2025.114240","article-title":"Numerical simulation and process parameter optimization of laser spot welding for ultra-thin sheets","volume":"193","author":"Peng","year":"2026","journal-title":"Opt Laser. Technol."},{"key":"10.1016\/j.engappai.2026.114622_bib26","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1016\/j.optlastec.2020.106194","article-title":"An improved methodology of melt pool monitoring of direct energy deposition processes","volume":"127","author":"Sampson","year":"2020","journal-title":"Opt. Laser Technol."},{"key":"10.1016\/j.engappai.2026.114622_bib27","doi-asserted-by":"crossref","first-page":"561","DOI":"10.1016\/j.cirp.2017.05.011","article-title":"Laser based additive manufacturing in industry and academia","volume":"66","author":"Schmidt","year":"2017","journal-title":"CIRP Ann.-Manuf. Technol."},{"key":"10.1016\/j.engappai.2026.114622_bib28","series-title":"Proceedings of the IEEE International Conference on Computer Vision","first-page":"618","article-title":"Grad-cam: visual explanations from deep networks via gradient-based localization","author":"Selvaraju","year":"2017"},{"key":"10.1016\/j.engappai.2026.114622_bib30","doi-asserted-by":"crossref","first-page":"271","DOI":"10.1016\/j.mattod.2021.03.020","article-title":"Directed energy deposition (DED) additive manufacturing: physical characteristics, defects, challenges and applications","volume":"49","author":"Svetlizky","year":"2021","journal-title":"Mater. Today"},{"key":"10.1016\/j.engappai.2026.114622_bib31","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.jmatprotec.2020.116996","article-title":"Investigation on coaxial visual characteristics of molten pool in laser-based directed energy deposition of AISI 316L steel","volume":"290","author":"Tang","year":"2021","journal-title":"J. Mater. Process. Technol."},{"key":"10.1016\/j.engappai.2026.114622_bib32","doi-asserted-by":"crossref","DOI":"10.1016\/j.ijleo.2021.167001","article-title":"An analytic parametric study of rounded laser pulse heating","volume":"240","author":"Turkyilmazoglu","year":"2021","journal-title":"Optik"},{"key":"10.1016\/j.engappai.2026.114622_bib33","doi-asserted-by":"crossref","first-page":"464","DOI":"10.1016\/j.actamat.2020.04.060","article-title":"Analysis of laser-induced microcracking in tungsten under additive manufacturing conditions: experiment and simulation","volume":"194","author":"Vrancken","year":"2020","journal-title":"Acta Mater."},{"key":"10.1016\/j.engappai.2026.114622_bib35","doi-asserted-by":"crossref","DOI":"10.1016\/j.optlastec.2022.108442","article-title":"Optimization of multistage femtosecond laser drilling process using machine learning coupled with molecular dynamics","volume":"156","author":"Wang","year":"2022","journal-title":"Opt Laser. Technol."},{"key":"10.1016\/j.engappai.2026.114622_bib36","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1016\/j.ymssp.2023.110440","article-title":"Gaussian process classification of melt pool motion for laser powder bed fusion process monitoring","volume":"198","author":"Wang","year":"2023","journal-title":"Mech. Syst. Signal Process."},{"key":"10.1016\/j.engappai.2026.114622_bib37","first-page":"11","article-title":"Prediction of spatiotemporal variations of deposit profiles and inter-track voids during laser directed energy deposition","volume":"34","author":"Wei","year":"2020","journal-title":"Addit. Manuf."},{"key":"10.1016\/j.engappai.2026.114622_bib38","article-title":"In-Situ quality intelligent classification of additively manufactured parts using a multi-sensor fusion based melt pool monitoring system","volume":"3","author":"Wu","year":"2024","journal-title":"Addit. Manufact. Front."},{"key":"10.1016\/j.engappai.2026.114622_bib39","first-page":"25","article-title":"Audio-visual cross-modality knowledge transfer for machine learning-based in-situ monitoring in laser additive manufacturing","volume":"101","author":"Xie","year":"2025","journal-title":"Addit. Manuf."},{"key":"10.1016\/j.engappai.2026.114622_bib40","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1016\/j.jmapro.2025.01.051","article-title":"Quantitative analysis of laser processing mode transformation process based on the multi-dimensional time-frequency characteristics of plume morphology","volume":"135","author":"Xie","year":"2025","journal-title":"J. Manuf. Process."},{"key":"10.1016\/j.engappai.2026.114622_bib41","doi-asserted-by":"crossref","first-page":"486","DOI":"10.1016\/j.jmapro.2021.12.030","article-title":"Using convolutional neural networks to classify melt pools in a pulsed selective laser melting process","volume":"74","author":"Xing","year":"2022","journal-title":"J. Manuf. Process."},{"key":"10.1016\/j.engappai.2026.114622_bib42","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1016\/j.isatra.2018.07.021","article-title":"In situ monitoring of selective laser melting using plume and spatter signatures by deep belief networks","volume":"81","author":"Ye","year":"2018","journal-title":"ISA Trans."},{"key":"10.1016\/j.engappai.2026.114622_bib43","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1016\/j.jmapro.2023.03.011","article-title":"Deep learning based real-time and in-situ monitoring of weld penetration: where we are and what are needed revolutionary solutions?","volume":"93","author":"Yu","year":"2023","journal-title":"J. Manuf. Process."},{"key":"10.1016\/j.engappai.2026.114622_bib44","doi-asserted-by":"crossref","first-page":"458","DOI":"10.1016\/j.matdes.2018.07.002","article-title":"Extraction and evaluation of melt pool, plume and spatter information for powder-bed fusion AM process monitoring","volume":"156","author":"Zhang","year":"2018","journal-title":"Mater. Des."},{"key":"10.1016\/j.engappai.2026.114622_bib45","first-page":"497","article-title":"In-Process monitoring of porosity during laser additive manufacturing process","volume":"28","author":"Zhang","year":"2019","journal-title":"Addit. Manuf."},{"key":"10.1016\/j.engappai.2026.114622_bib46","doi-asserted-by":"crossref","first-page":"1732","DOI":"10.1109\/TMECH.2019.2916984","article-title":"Simultaneous monitoring of penetration status and joint tracking during laser keyhole welding","volume":"24","author":"Zhang","year":"2019","journal-title":"IEEE-Asme Trans. Mechatron."},{"key":"10.1016\/j.engappai.2026.114622_bib47","first-page":"263","article-title":"In-situ monitoring of laser-based PBF via off-axis vision and image processing approaches","volume":"25","author":"Zhang","year":"2019","journal-title":"Addit. Manuf."},{"key":"10.1016\/j.engappai.2026.114622_bib48","doi-asserted-by":"crossref","DOI":"10.1016\/j.optlastec.2021.107688","article-title":"Optimization of low-power femtosecond laser trepan drilling by machine learning and a high-throughput multi-objective genetic algorithm","volume":"148","author":"Zhang","year":"2022","journal-title":"Opt Laser. Technol."},{"issue":"1","key":"10.1016\/j.engappai.2026.114622_bib49","doi-asserted-by":"crossref","first-page":"449","DOI":"10.1007\/s10845-022-02058-0","article-title":"Accelerating ultrashort pulse laser micromachining process comprehensive optimization using a machine learning cycle design strategy integrated with a physical model","volume":"35","author":"Zhang","year":"2024","journal-title":"J. Intell. Manuf."},{"key":"10.1016\/j.engappai.2026.114622_bib50","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1016\/j.ymssp.2024.111993","article-title":"In-situ quality inspection based on coaxial melt pool images for laser powder bed fusion with depth graph network guided by prior knowledge","volume":"224","author":"Zhang","year":"2025","journal-title":"Mech. Syst. Signal Process."},{"key":"10.1016\/j.engappai.2026.114622_bib51","first-page":"1","article-title":"Off-axis four-reflection optical structure for lightweight single-band bathymetric LiDAR","volume":"61","author":"Zhou","year":"2023","journal-title":"IEEE Trans. Geosci. Rem. Sens."},{"key":"10.1016\/j.engappai.2026.114622_bib52","first-page":"1","article-title":"Adaptive adjustment for laser energy and PMT gain through self-feedback of echo data in bathymetric LiDAR","volume":"62","author":"Zhou","year":"2024","journal-title":"IEEE Trans. Geosci. Rem. Sens."}],"container-title":["Engineering Applications of Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0952197626009036?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0952197626009036?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T23:33:18Z","timestamp":1778283198000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0952197626009036"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7]]},"references-count":51,"alternative-id":["S0952197626009036"],"URL":"https:\/\/doi.org\/10.1016\/j.engappai.2026.114622","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":"High-fidelity imaging of laser-directed energy deposition via a dual-stage strategy of exposure optimization and adaptive enhancement","name":"articletitle","label":"Article Title"},{"value":"Engineering Applications of Artificial Intelligence","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.engappai.2026.114622","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":"114622"}}