Publications - 'M'
Publications 26 - 50 de 1879
| Titre | DOI |
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Machine Learning and Digital Heritage: The CEPROQHA Project Perspective A. Belhi; H. Gasmi; A. Bouras; T. Alfaqheri; A.Solomon Aondoakaa; A.H. Sadka; S. Foufou 2020 |
10.1007/978-981-32-9343-4_29 |
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Machine Learning Approaches for Activity Recognition and/or Activity Prediction in Locomotion Assistive Devices-A Systematic Review F. Labarriere; E. Thomas; L. Calistri; V. Optasanu; M. Gueugnon; P. Ornetti; D. Laroche 2020 |
10.3390/s20216345 |
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Machine Learning for Better Prognostic Stratification and Driver Gene Identification Using Somatic Copy Number Variations in Anaplastic Oligodendroglioma S. Rosenberg; F. Ducray; A. Alentorn; C. Dehais; N. Elarouci; A. Kamoun; Y. Marie; M.L. Tanguy; A. de Reynies; K. Mokhtari; D. Figarella-Branger; J.Y. Delattre; A. Idbaih; C. Adam; M. Andraud; M.H. Aubriot-Lorton; L. Bauchet; P. Beauchesne; L. Bekaert; C. Blechet; M. Campone; A. Carpentier; I. Carpiuc; D. Cazals-Hatem; B. Lhermitte; D. Chiforeanu; O. Chinot; E. Cohen-Moyal; P. Colin; T. Cruel; P. Dam-Hieu; C. Desenclos; N. Desse; F. Dhermain; M.D. Diebold; S. Eimer; T. Faillot; M. Fesneau; D. Fontaine; S. Gaillard; F. Forest; G. Gauchotte; C. Gaultier; F. Ghiringhelli; C. Godfraind; E.Marcel Gueye; S. Elouadhani-Hamdi; J. Honnorat; T. Khallil; F. Labrousse; W. Lahiani; O. Langlois; A. Laquerriere; D. Larrieu-Ciron; E. Lechapt-Zalcman; H. Loiseau; S. Lopez; D. Loussouarn; C.A. Maurage; P. Menei; M.Ionella Mihai; S. Milin; M.Janette Mo Fotso; G. Noel; F. Parker; A. Petit; I. Quintin-Roue; C. Ramirez; A. Rousseau; C. Rousselot-Denis; D. Ricard; P. Richard; V. Rigau; G. Runavot; H. Sevestre; M.Christine Tortel; F. Vandenbos; E. Vauleon; C. Villa; I. Zemmoura; C. Desenclos; H. Sevestre; P. Menei; A. Rousseau; T. Cruel; S. Lopez; ; A. Petit; C. Adam; F. Parker; A. Carpentier; P. Dam-Hieu; I. Quintin-Roue; S. Eimer; H. Loiseau; L. Bekaert; E. Lechapt-Zalcman; C. Godfraind; T. Khallil; D. Cazals-Hatem; T. Faillot; C. Gaultier; M.C. Tortel; I. Carpiuc; P. Richard; W. Lahiani; H. Aubriot-Lorton; F. Ghiringhelli; C.A. Maurage; C. Ramirez; E.M. Gueye; F. Labrousse; F. Ducray; A. Jouvet; D. Figarella-Branger; O. Chinot; L. Bauchet; V. Rigau; P. Beauchesne; G. Gauchotte; M. Campone; D. Loussouarn; D. Fontaine; F. Vandenbos-Burel; C. Blechet; M. Fesneau; C. Dehais; J.Y. Delattre; S. Elouadhani-Hamdi; D. Ricard; D. Larrieu-Ciron; S. Milin; P. Colin; M.D. Diebold; D. Chiforeanu; E. Vauleon; O. Langlois; A. Laquerriere; F. Forest; M.J. Motso-Fotso; M. Andraud; G. Runavot; B. Lhermitte; G. Noel; S. Gaillard; C. Villa; N. Desse; E. Cohen-Moyal; E. Uro-Coste; F. Dhermain; P.O.L.A. Network 2018 |
10.1634/theoncologist.2017-0495 |
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Machine learning for rapid mapping of archaeological structures made of dry stones - Example of burial monuments from the Khirgisuur culture, Mongolia - F. Monna; J. Magail; T. Rolland; N. Navarro; J. Wilczek; J.O. Gantulga; Y. Esin; L. Granjon; A.C. Allard; C. Chateau-Smith 2020 |
10.1016/j.culher.2020.01.002 |
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Machine learning models to predict the response to anti-cancer therapy in metastatic melanoma patients. R. Goussault; C. Frenard; E. Maubec; P. Muller; L. Martin; D. Legoupil; F. Aubin; J. De Quatrebarbes; T. Jouary; A. Hervieu; L. Machet; E. Varey; P. Lecerf; F. Vrignaud; A. Khammari; B. Dreno 2020 |
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Machine Learning of Microbial Interactions Using Abductive ILP and Hypothesis Frequency/Compression Estimation D. Barroso-Bergada; A. Tamaddoni-Nezhad; S.H. Muggleton; C. Vacher; N. Galic; D.A. Bohan 2022 |
10.1007/978-3-030-97454-1_3 |
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Machine learning predictions of trophic status indicators and plankton dynamic in coastal lagoons B. Bejaoui; E. Ottaviani; E. Barelli; B. Ziadi; A. Dhib; M. Lavoie; C. Gianluca; S. Turki; C. Solidoro; L. Aleya 2018 |
10.1016/j.ecolind.2018.08.041 |
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Machine Learning Techniques for Automatic Depression Assessment A. Maridaki; A. Pampouchidou; K. Marias; M. Tsiknakis 2018 |
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Machine Learning Techniques for Automatic Depression Assessment A. Maridaki; A. Pampouchidou; K. Marias; M. Tsiknakis 2018 |
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Machine learning techniques for diabetic macular edema (DME) classification on SD-OCT images K. Alsaih; G. Lemaitre; M. Rastgoo; J. Massich; D. Sidibe; F. Meriaudeau 2017 |
10.1186/s12938-017-0352-9 |
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Machine Learning Techniques for Intrusion Detection: A Comparative Analysis Y. Hamid; M. Sugumaran; L. Journaux 2016 |
10.1145/2980258.2980378 |
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Machine learning with screens for detecting bid-rigging cartels M. Huber; D. Imhof 2019 |
10.1016/j.ijindorg.2019.04.002 |
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Machine learning-based forecasting of firemen ambulances' turnaround time in hospitals, considering the COVID-19 impact S. Cerna; H.H. Arcolezi; C. Guyeux; G. Royer-Fey; C. Chevallier 2021 |
10.1016/j.asoc.2021.107561 |
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Machine Learning-Based Reverse Modeling Approach for Rapid Tool Shape Optimization in Die-Sinking Micro Electro Discharge Machining A. Surleraux; R. Lepert; J.P. Pernot; P. Kerfriden; S. Bigot 2020 |
10.1115/1.4045956 |
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Machine Learning-Evolutionary Algorithm Enabled Design for 4D-Printed Active Composite Structures X. Sun; L. Yue; L. Yu; H. Shao; X. Peng; K. Zhou; F. Demoly; R. Zhao; J. Qi 2022 |
10.1002/adfm.202109805 |
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Machine vision for timber grading singularities detection and applications M.Mazen Hittawe; D. Sidibe; O. Beya; F. Meriaudeau 2017 |
10.1117/1.JEI.26.6.063015 |
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Machine-learning based design of active composite structures for 4D printing C.M. Hamel; D.J. Roach; K.N. Long; F. Demoly; M.L. Dunn; J. Qi 2019 |
10.1088/1361-665X/ab1439 |
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Macitentan reduces progression of TGF-beta 1-induced pulmonary fibrosis and pulmonary hypertension P.S. Bellaye; T. Yanagihara; E. Granton; S. Sato; C. Shimbori; C. Upagupta; J. Imani; N. Hambly; K. Ask; J. Gauldie; M. Iglarz; M. Kolb 2018 |
10.1183/13993003.01857-2017 |
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Macro and Micronutrient Storage in Plants and Their Remobilization When Facing Scarcity: The Case of Drought P. Etienne; S. Diquelou; M. Prudent; C. Salon; A. Maillard; A. Ourry 2018 |
10.3390/agriculture8010014 |
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Macro Models, Micro Models and Network-based Coupling A. Banos; C. Lang; N. Marilleau 2017 |
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Macro-micromanipulation platform for inner ear drug delivery W. Amokrane; K. Belharet; M. Souissi; B. Grayeli; A. Ferreira 2018 |
10.1016/j.robot.2018.05.002 |
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MACROBICYCLIC AND MACROTRICYCLIC DERIVATIVES OF N,N `,N `', N `''-TETRASUBSTITUTED CYCLEN AND CYCLAM S.M. Kobelev; A.D. Averin; A.K. Buryak; A.I. Voyk; V.P. Kukhar; F. Denat; R. Guilard; I.P. Beetskayal 2015 |
10.3987/COM-14-S(K)71 |
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Macrocognition through the Multiscale Enaction Model (MEM) Lens: Identification of a Blind Spot of Macrocognition Research E. Laurent; R. Bianchi 2016 |
10.3389/fpsyg.2016.01123 |
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Macroecological and macroevolutionary patterns emerge in the universe of GNU/Linux operating systems P. Keil; A.A.M. MacDonald; K.S. Ramirez; J.M. Bennett; G.E. Garcia-Pena; B. Yguel; B. Bourgeois; C. Meyer 2018 |
10.1111/ecog.03424 |
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Macroepibenthic communities at the tip of the Antarctic Peninsula, an ecological survey at different spatial scales J. Gutt; M.C. Alvaro; A. Barco; A. Boehmer; A. Bracher; B. David; C. De Ridder; B. Dorschel; M. Eleaume; D. Janussen; D. Kersken; P.J. Lopez-Gonzalez; I. Martinez-Baraldes; M. Schroeder; A. Segelken-Voigt; N. Teixido 2016 |
10.1007/s00300-015-1797-6 |