Publications
Publications 7926 - 7950 de 33557
| Titre | DOI |
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Deep deoxidization from liquid iron by hydrogen plasma arc melting X. Guo; J. Yu; Y. Zhang; L. Liu; X. Li; H. Liao; Z. Ren 2018 |
10.1016/j.ijhydene.2018.04.035 |
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Deep insight into electron transport and photovoltaic parameters in DSSCs K. Hamdani; M. Adnane; S. Sam; D. Chaumont; S. Belhousse; F.Z. Tighilt; K. Lasmi; A. Hamrani 2019 |
10.1680/jemmr.18.00088 |
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Deep learning aided OFDM receiver for underwater acoustic communications Y. Zhang; C. Li; H. Wang; J. Wang; F. Yang; F. Meriaudeau 2022 |
10.1016/j.apacoust.2021.108515 |
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Deep Learning and Cultural Heritage: The CEPROQHA Project Case Study A. Belhi; H. Gasmi; A.Khalid Al-Ali; A. Bouras; S. Foufou; X. Yu; H. Zhang 2019 |
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Deep learning approach for artefacts correction on photographic films S. David; B. Marc; F. David 2019 |
10.1117/12.2521421 |
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Deep learning architectures analysis for age-related macular degeneration segmentation on optical coherence tomography scans K. Alsaih; M.Z. Yusoff; T.B. Tang; I. Faye; F. Meriaudeau 2020 |
10.1016/j.cmpb.2020.105566 |
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Deep Learning Based Cardiac MRI Segmentation: Do We Need Experts? Y. Skandarani; P.M. Jodoin; A. Lalande 2021 |
10.3390/a14070212 |
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Deep Learning for B5G Open Radio Access Network: Evolution, Survey, Case Studies, and Challenges B. Brik; K. Boutiba; A. Ksentini 2022 |
10.1109/OJCOMS.2022.3146618 |
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Deep Learning for Fault Diagnosis based on short-time Fourier transform T. Benkedjouh; N. Zerhouni; S. Rechak 2018 |
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Deep Learning in the Biomedical Applications: Recent and Future Status R. Zemouri; N. Zerhouni; D. Racoceanu 2019 |
10.3390/app9081526 |
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Deep learning reconstruction versus iterative reconstruction for cardiac CT angiography in a stroke imaging protocol: reduced radiation dose and improved image quality A. Bernard; P.O. Comby; B. Lemogne; K. Haioun; F. Ricolfi; O. Chevallier; R. Loffroy 2021 |
10.21037/qims-20-626 |
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Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved? O. Bernard; A. Lalande; C. Zotti; F. Cervenansky; X. Yang; P.A. Heng; I. Cetin; K. Lekadir; O. Camara; M.Angel Gonz Ballester; G. Sanroma; S. Napel; S. Petersen; G. Tziritas; E. Grinias; M. Khened; V.Alex Kollerathu; G. Krishnamurthi; M.M. Rohe; X. Pennec; M. Sermesant; F. Isensee; P. Jaeger; K.H. Maier-Hein; P.M. Full; I. Wolf; S. Engelhardt; C.F. Baumgartner; L.M. Koch; J.M. Wolterink; I. Isgum; Y. Jang; Y. Hong; J. Patravali; S. Jain; O. Humbert; P.M. Jodoin 2018 |
10.1109/TMI.2018.2837502 |
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Deep Learning Techniques for Depression Assessment M.Ahmad Hazi S'adan; A. Pampouchidou; F. Meriaudeau 2018 |
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Deep Learning Techniques for Depression Assessment M.Ahmad Hazi S'adan; A. Pampouchidou; F. Meriaudeau 2018 |
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Deep learning to detect built cultural heritage from satellite imagery.-Spatial distribution and size of vernacular houses in Sumba, Indonesia F. Monna; T. Rolland; A. Denaire; N. Navarro; L. Granjon; R. Barbe; C. Chateau-Smith 2021 |
10.1016/j.culher.2021.10.004 |
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Deep Learning Versus Iterative Reconstruction for CT Pulmonary Angiography in the Emergency Setting: Improved Image Quality and Reduced Radiation Dose M. Lenfant; O. Chevallier; P.O. Comby; G. Secco; K. Haioun; F. Ricolfi; B. Lemogne; R. Loffroy 2020 |
10.3390/diagnostics10080558 |
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Deep Learning-Based Real-time Object Detection in Inland Navigation W. Hammedi; M. Ramirez-Martinez; P. Brunet; S.Mohammed Senouci; M.Ayoub Messous 2019 |
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Deep Learning-Based Real-time Object Detection in Inland Navigation W. Hammedi; M. Ramirez-Martinez; P. Brunet; S.Mohammed Senouci; M.Ayoub Messous 2019 |
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Deep LSTM Enhancement for RUL Prediction Using Gaussian Mixture Models M. Sayah; D. Guebli; Z. Noureddine; A. Masry 2021 |
10.3103/S0146411621010089 |
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Deep multimodal fusion for semantic image segmentation: A survey Y. Zhang; D. Sidibe; O. Morel; F. Meriaudeau 2021 |
10.1016/j.imavis.2020.104042 |
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Deep recurrent neural network-based autoencoder for photoplethysmogram artifacts filtering J. Azar; A. Makhoul; R. Couturier; J. Demerjian 2021 |
10.1016/j.compeleceng.2021.107065 |
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Deep SDSS optical spectroscopy of distant halo stars I. Atmospheric parameters and stellar metallicity distribution A. Prieto; E. Fernandez-Alvar; K.J. Schlesinger; Y.S. Lee; H.L. Morrison; D.P. Schneider; T.C. Beers; D. Bizyaev; G. Ebelke; E. Malanushenko; V. Malanushenko; D. Oravetz; K. Pan; A. Simmons; J. Simmerer; J. Sobeck; A.C. Robin 2014 |
10.1051/0004-6361/201424053 |
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Deep SDSS optical spectroscopy of distant halo stars II. Iron, calcium, and magnesium abundances E. Fernandez-Alvar; A. Prieto; K.J. Schlesinger; T.C. Beers; A.C. Robin; D.P. Schneider; Y.S. Lee; D. Bizyaev; G. Ebelke; E. Malanushenko; V. Malanushenko; D. Oravetz; K. Pan; A. Simmons 2015 |
10.1051/0004-6361/201425455 |
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Deep-Learning F-18-FDG Uptake Classification Enables Total Metabolic Tumor Volume Estimation in Diffuse Large B-Cell Lymphoma N. Capobianco; M. Meignan; A.S. Cottereau; L. Vercellino; L. Sibille; B. Spottiswoode; S. Zuehlsdorff; O. Casasnovas; C. Thieblemont; I. Buvat 2021 |
10.2967/jnumed.120.242412 |
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Deeper insight into protease-sensitive ``covalent-assembly'' fluorescent probes for practical biosensing applications K. Renault; S. Debieu; J.A. Richard; A. Romieu 2019 |
10.1039/c9ob01773a |