| Advanced steel microstructural classification by deep learning methods SM Azimi, D Britz, M Engstler, M Fritz, F Mücklich Scientific reports 8 (1), 1-14, 2018 | 149 | 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 | 42 | 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 | 32 | 2019 |
| 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 | 19 | 2018 |
| 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 | 16 | 2016 |
| 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 | 13 | 2017 |
| 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 | 9 | 2017 |
| 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 | 8 | 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 (3), 755-765, 2020 | 7 | 2020 |
| Why we need all dimensions to solve both very old and very new questions in materials at the micro-, nano-and atomic scales F Mücklich, M Engstler, D Britz, J Barrirero, P Rossi Practical Metallography 52 (9), 507-524, 2015 | 7 | 2015 |
| 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 | 6 | 2020 |
| 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 | 6 | 2016 |
| Investigation of Austenite Evolution in Low-Carbon Steel by Combining Thermo-Mechanical Simulation and EBSD Data S Weyand, D Britz, D Rupp, F Mücklich Materials Performance and Characterization 4 (3), 322-340, 2015 | 5 | 2015 |
| 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 | 4 | 2020 |
| Evaluation of the etching process for analysis of secondary carbides in HCCI by optical and confocal laser microscopy MA Guitar, A Scheid, D Britz, F Muecklich Practical Metallography 56 (4), 246-261, 2019 | 4 | 2019 |
| Serial Sectioning Techniques–a Versatile Method for Three-Dimensional Microstructural Imaging F Mücklich, M Engstler, D Britz, J Gola Practical Metallography 55 (8), 569-578, 2018 | 4 | 2018 |
| Application of trainable segmentation to microstructural images using low-alloy steels as an example M Müller, D Britz, F Mücklich Practical Metallography 57 (5), 337-358, 2020 | 2 | 2020 |
| MACHINE LEARNING FOR MICROSTRUCTURE CLASSIFICATION: HOW TO ASSIGN THE GROUND TRUTH IN THE MOST OBJECTIVE WAY M Mueller, D Britz, F Muecklich ADVANCED MATERIALS & PROCESSES 179 (1), 16-21, 2021 | 1 | 2021 |
| Opening the door to fundamental understanding of structure and color metallography-a correlative microscopy study on steel D Britz, A Hegetschweiler, F Mücklich Microscopy and Microanalysis 20 (S3), 834-835, 2014 | 1 | 2014 |
| A Deep Learning Approach for Complex Microstructure Inference A Durmaz, M Müller, B Lei, A Thomas, D Britz, E Holm, C Eberl, ... | | 2021 |
