{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T04:22:37Z","timestamp":1782793357927,"version":"3.54.5"},"reference-count":86,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/100006602","name":"a research grant from the Air Force Research Laboratory\/CATIE","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100006602","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2021]]},"DOI":"10.1109\/access.2021.3105362","type":"journal-article","created":{"date-parts":[[2021,8,16]],"date-time":"2021-08-16T20:21:44Z","timestamp":1629145304000},"page":"115100-115114","source":"Crossref","is-referenced-by-count":53,"title":["DLAM: Deep Learning Based Real-Time Porosity Prediction for Additive Manufacturing Using Thermal Images of the Melt Pool"],"prefix":"10.1109","volume":"9","author":[{"given":"Samson","family":"Ho","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenlu","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wesley","family":"Young","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Matthew","family":"Buchholz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Saleh Al","family":"Jufout","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Khalil","family":"Dajani","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Linkan","family":"Bian","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohammad","family":"Mozumdar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.81"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"ref71","first-page":"1097","article-title":"ImageNet classification with deep convolutional neural networks","volume":"25","author":"krizhevsky","year":"2012","journal-title":"Proc Adv Neural Inf Process Syst (NIPS)"},{"key":"ref70","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1007\/978-3-642-46466-9_18","article-title":"Neocognitron: A self-organizing neural network model for a mechanism of visual pattern recognition","author":"fukushima","year":"1982","journal-title":"Competition and Cooperation in Neural Nets"},{"key":"ref76","article-title":"Pythia v0.1: The winning entry to the VQA challenge 2018","author":"jiang","year":"2018","journal-title":"arXiv 1807 09956"},{"key":"ref77","doi-asserted-by":"publisher","DOI":"10.1109\/72.788640"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.91"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1007\/s00170-014-6214-8"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298932"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1080\/24725854.2019.1659525"},{"key":"ref78","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref79","doi-asserted-by":"publisher","DOI":"10.1016\/j.tics.2007.09.009"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1016\/j.addma.2018.05.004"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijmachtools.2019.04.002"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmatprotec.2017.08.012"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1107\/S1600577518009554"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1016\/j.addma.2018.05.032"},{"key":"ref36","article-title":"Melt pool monitoring using fuzzy based anomaly detection in laser beam melting","author":"boos","year":"0"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1080\/24725854.2017.1417656"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmsy.2018.04.001"},{"key":"ref60","article-title":"BERT: Pre-training of deep bidirectional transformers for language understanding","author":"devlin","year":"2018","journal-title":"arXiv 1810 04805"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.2514\/1.T5774"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2012.2205597"},{"key":"ref63","first-page":"735","article-title":"Deep learning via hessian-free optimization","volume":"27","author":"martens","year":"2010","journal-title":"Proc ICML"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijmachtools.2020.103555"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-662-43505-2_28"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-019-10009-2"},{"key":"ref65","article-title":"Understanding the effective receptive field in deep convolutional neural networks","author":"luo","year":"2017","journal-title":"arXiv 1701 04128"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.5120\/ijca2015906480"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-017-03761-2"},{"key":"ref67","article-title":"Understanding random forests","volume":"10","author":"louppe","year":"2014"},{"key":"ref68","article-title":"Fast cubic spline interpolation","author":"hornbeck","year":"2020","journal-title":"arXiv 2001 09253"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298958"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1080\/17452759.2015.1111519"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.promfg.2019.06.089"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.3390\/ma12132052"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1016\/j.addma.2019.100939"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.3390\/jmmp2030063"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.2351\/1.5063185"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-019-10973-9"},{"key":"ref26","article-title":"Discovering universal scaling laws in 3D printing of metals with genetic programming and dimensional analysis","author":"gan","year":"2020","journal-title":"arXiv 2005 00117"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.2351\/1.5040624"},{"key":"ref50","first-page":"448","article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","author":"ioffe","year":"2015","journal-title":"Proc ICML"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.308"},{"key":"ref59","article-title":"Attention is all you need","author":"vaswani","year":"2017","journal-title":"arXiv 1706 03762"},{"key":"ref58","article-title":"Neural machine translation by jointly learning to align and translate","author":"bahdanau","year":"2014","journal-title":"arXiv 1409 0473"},{"key":"ref57","article-title":"Sequence to sequence learning with neural networks","author":"sutskever","year":"2014","journal-title":"arXiv 1409 3215 [cs]"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/D14-1162"},{"key":"ref55","article-title":"Efficient estimation of word representations in vector space","author":"mikolov","year":"2013","journal-title":"arXiv 1301 3781 [cs]"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/TBDATA.2016.2573280"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2014.12.061"},{"key":"ref52","first-page":"1","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2014","journal-title":"Proc ICLR"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.mfglet.2020.03.014"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1063\/1.4935926"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1016\/j.addma.2019.05.030"},{"key":"ref12","article-title":"Additive manufacturing of Ti6Al4 V alloy: A review","volume":"164","author":"liu","year":"2019","journal-title":"Mater Design"},{"key":"ref13","first-page":"55","article-title":"Microstructural modeling of thermally-driven $\\beta$\n grain growth, lamellae & martensite in Ti-6Al-4 V","volume":"10","author":"villa","year":"2020","journal-title":"Model Numer Simul Mater Sci"},{"key":"ref14","article-title":"Metallurgical and mechanical modelling of Ti-6Al-4V for welding applications","author":"villa","year":"2016"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1063\/1.1737476"},{"key":"ref82","article-title":"Reading digits in natural images with unsupervised feature learning","author":"netzer","year":"2011"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/s10765-005-0001-6"},{"key":"ref81","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.3390\/ma11081318"},{"key":"ref84","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2577031"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.msea.2019.138456"},{"key":"ref83","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.169"},{"key":"ref19","first-page":"3","article-title":"Part and material properties in selective laser melting of metals","author":"kruth","year":"2010","journal-title":"Proc 16th Int Symp Electromachining (ISEM)"},{"key":"ref80","article-title":"Learning multiple layers of features from tiny images","author":"krizhevsky","year":"2009"},{"key":"ref4","article-title":"Microstructure phase transformation Ti-6Al-4V","author":"pederson","year":"2002"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1002\/adhm.201701161"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3062618"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijft.2021.100091"},{"key":"ref85","doi-asserted-by":"publisher","DOI":"10.1613\/jair.953"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.actaastro.2018.06.063"},{"key":"ref86","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.123"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.actaastro.2014.11.036"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2015.2389824"},{"key":"ref9","author":"devries","year":"1991","journal-title":"Analysis of Material Removal Processes"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmapro.2021.03.002"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1115\/1.4037571"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-020-75131-4"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1115\/1.4043898"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1016\/j.addma.2019.100946"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1016\/j.matdes.2019.108110"},{"key":"ref43","article-title":"Measurement of process dynamics through coaxially aligned high speed near-infrared imaging in laser powder bed fusion additive manufacturing","volume":"10214","author":"fox","year":"2017","journal-title":"Proc SPIE"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"https:\/\/ieeexplore.ieee.org\/ielam\/6287639\/9312710\/9514863-aam.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/9312710\/09514863.pdf?arnumber=9514863","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,8]],"date-time":"2022-04-08T18:53:41Z","timestamp":1649444021000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9514863\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":86,"URL":"https:\/\/doi.org\/10.1109\/access.2021.3105362","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]}}}