| Advanced steel microstructural classification by deep learning methods SM Azimi, D Britz, M Engstler, M Fritz, F Mücklich Scientific reports 8 (1), 2128, 2018 | 466 | 2018 |
| Advanced microstructure classification by data mining methods J Gola, D Britz, T Staudt, M Winter, AS Schneider, M Ludovici, F Mücklich Computational Materials Science 148, 324-335, 2018 | 112 | 2018 |
| Objective microstructure classification by support vector machine (SVM) using a combination of morphological parameters and textural features for low carbon steels J Gola, J Webel, D Britz, A Guitar, T Staudt, M Winter, F Mücklich Computational Materials Science 160, 186-196, 2019 | 96 | 2019 |
| A deep learning approach for complex microstructure inference AR Durmaz, M Müller, B Lei, A Thomas, D Britz, EA Holm, C Eberl, ... Nature communications 12 (1), 6272, 2021 | 85 | 2021 |
| Classification of bainitic structures using textural parameters and machine learning techniques M Müller, D Britz, L Ulrich, T Staudt, F Mücklich Metals 10 (5), 630, 2020 | 51 | 2020 |
| A new analysis approach based on Haralick texture features for the characterization of microstructure on the example of low-alloy steels J Webel, J Gola, D Britz, F Mücklich materials Characterization 144, 584-596, 2018 | 45 | 2018 |
| The effect of thermal processing and chemical composition on secondary carbide precipitation and hardness in high-chromium cast irons MA Guitar, UP Nayak, D Britz, F Mücklich International Journal of Metalcasting 14, 755-765, 2020 | 40 | 2020 |
| Addressing materials’ microstructure diversity using transfer learning A Goetz, AR Durmaz, M Müller, A Thomas, D Britz, P Kerfriden, C Eberl npj Computational Materials 8 (1), 27, 2022 | 29 | 2022 |
| Tracing microalloy precipitation in Nb-Ti HSLA steel during austenite conditioning J Webel, A Herges, D Britz, E Detemple, V Flaxa, H Mohrbacher, ... Metals 10 (2), 243, 2020 | 29 | 2020 |
| A correlative approach to capture and quantify substructures by means of image registration D Britz, J Webel, J Gola, F Mücklich Practical Metallography 54 (10), 685-696, 2017 | 29 | 2017 |
| Reproducible surface contrasting and orientation correlation of low-carbon steels by time-resolved beraha color etching D Britz, A Hegetschweiler, M Roberts, F Mücklich Materials Performance and Characterization 5 (5), 553-563, 2016 | 28 | 2016 |
| Secondary carbides in high chromium cast irons: An alternative approach to their morphological and spatial distribution characterization MA Guitar, A Scheid, S Suárez, D Britz, MD Guigou, F Mücklich Materials Characterization 144, 621-630, 2018 | 23 | 2018 |
| Identifying and quantifying microstructures in low-alloyed steels: a correlative approach D Britz, J Webel, A Schneider, F Mücklich Metallurgia Italiana 3, 5-10, 2017 | 18 | 2017 |
| Influence of porosity and impurities on the thermal conductivity of pressure-less sintered Cu powder green bodies J Ott, A Burghardt, D Britz, F Mücklich Powder Metallurgy 64 (2), 85-96, 2021 | 16 | 2021 |
| Microstructural classification of bainitic subclasses in low-carbon multi-phase steels using machine learning techniques M Müller, D Britz, T Staudt, F Mücklich Metals 11 (11), 1836, 2021 | 14 | 2021 |
| Machine Learning for Microstructure Classification: How to assign the ground truth in the most objective way M Müller, D Britz, F Mücklich AM&P Technical Articles 179 (1), 16-21, 2021 | 14 | 2021 |
| Quantitative analysis of mixed niobium-titanium carbonitride solubility in HSLA steels based on atom probe tomography and electrical resistivity measurements J Webel, H Mohrbacher, E Detemple, D Britz, F Mücklich journal of materials research and technology 18, 2048-2063, 2022 | 13 | 2022 |
| Efficient reconstruction of prior austenite grains in steel from etched light optical micrographs using deep learning and annotations from correlative microscopy BI Bachmann, M Müller, D Britz, AR Durmaz, M Ackermann, O Shchyglo, ... Frontiers in materials 9, 1033505, 2022 | 11 | 2022 |
| Scale-bridging microstructural analysis–a correlative approach to microstructure quantification combining microscopic images and EBSD data M Müller, D Britz, F Mücklich Practical Metallography 58 (7), 408-426, 2021 | 11 | 2021 |
| Effect of indentation temperature on nickel-titanium indentation-induced two-way shape-memory surfaces SA Brinckmann, M Frensemeier, CM Laursen, HJ Maier, D Britz, ... Materials Science and Engineering: A 675, 253-261, 2016 | 11 | 2016 |
