| N6-methyldeoxyadenosine directs nucleosome positioning in Tetrahymena DNA GZ Luo, Z Hao, L Luo, M Shen, D Sparvoli, Y Zheng, Z Zhang, X Weng, ... Genome biology 19, 1-12, 2018 | 57 | 2018 |
| A deep learning based automatic defect analysis framework for In-situ TEM ion irradiations M Shen, G Li, D Wu, Y Yaguchi, JC Haley, KG Field, D Morgan Computational Materials Science 197, 110560, 2021 | 52 | 2021 |
| Multi defect detection and analysis of electron microscopy images with deep learning M Shen, G Li, D Wu, Y Liu, JRC Greaves, W Hao, NJ Krakauer, L Krudy, ... Computational Materials Science 199, 110576, 2021 | 50 | 2021 |
| Performance and limitations of deep learning semantic segmentation of multiple defects in transmission electron micrographs R Jacobs*, M Shen*, Y Liu*, W Hao, X Li, R He, JRC Greaves, D Wang, ... Cell Reports Physical Science 3 (5), 2022 | 31 | 2022 |
| Chemically driven fluid transport in long microchannels M Shen, F Ye, R Liu, K Chen, M Yang, M Ripoll The journal of chemical physics 145 (12), 2016 | 24 | 2016 |
| Assessing graph‐based deep learning models for predicting flash point X Sun, NJ Krakauer, A Politowicz, WT Chen, Q Li, Z Li, X Shao, A Sunaryo, ... Molecular Informatics 39 (6), 1900101, 2020 | 22 | 2020 |
| Machine learning principles applied to CT radiomics to predict mucinous pancreatic cysts AM Awe, MM Vanden Heuvel, T Yuan, VR Rendell, M Shen, A Kampani, ... Abdominal Radiology, 1-11, 2022 | 14 | 2022 |
| Evaluation of radiomics and machine learning in identification of aggressive tumor features in renal cell carcinoma (RCC) S Gurbani, D Morgan, V Jog, L Dreyfuss, M Shen, A Das, EJ Abel, ... Abdominal Radiology 46, 4278-4288, 2021 | 13 | 2021 |
| Harmonization and targeted feature dropout for generalized segmentation: Application to multi-site traumatic brain injury images Y Liu, GR Kirk, BM Nacewicz, MA Styner, M Shen, D Nie, N Adluru, ... Domain Adaptation and Representation Transfer and Medical Image Learning …, 2019 | 12 | 2019 |
| Development and deployment of automated machine learning detection in electron microcopy experiments KG Field, R Jacobs, M Shen, M Lynch, P Patki, C Field, D Morgan Microscopy and Microanalysis 27 (S1), 2136-2137, 2021 | 10 | 2021 |
| Mesoscale simulation of self-diffusiophoretic microrotor S Ming-Ren, L Rui, H Mei-Ying, Y Ming-Cheng, C Ke ACTA PHYSICA SINICA 65 (17), 2016 | 9 | 2016 |
| Rapid Characterization Methods for Accelerated Innovation for Nuclear Fuel Cladding KG Field, M Shen, CP Massey, KC Littrell, DD Morgan Microscopy and Microanalysis 26 (S2), 868-869, 2020 | 4 | 2020 |
| Diffusive-flux-driven microturbines by fore-and-aft asymmetric phoresis M Shen, R Liu, K Chen, M Yang Physical Review Applied 12 (3), 034051, 2019 | 4 | 2019 |
| Machine learning for interpreting coherent X-ray speckle patterns M Shen, D Sheyfer, TD Loeffler, SKRS Sankaranarayanan, ... Computational Materials Science 230, 112500, 2023 | 2 | 2023 |
| Exploring Generative Adversarial Networks for Image-to-Image Translation in STEM Simulation N Lawrence, M Shen, R Yin, C Feng, D Morgan arXiv preprint arXiv:2010.15315, 2020 | 2 | 2020 |
| Query Time Optimized Deep Learning Based Video Inference System M Shen, S Dong, X He arXiv preprint arXiv:2212.06905, 2022 | 1 | 2022 |
| Machine Learning Applications in Material Science Problems M Shen The University of Wisconsin-Madison, 2021 | 1 | 2021 |
| Automated Defect Detection in Electron Microscopy of Radiation Damage in Metals D Morgan, R Jacobs, M Shen, P Patki, M Lynch, K Field | | |
Dane MorganUniversity of Wisconsin, Materials Science在 wisc.edu 的电子邮件经过验证
