Image Segmentation using U-Net Architecture for Powder X-ray Diffraction Images

no code implementations • 24 Oct 2023 • Howard Yanxon, Eric Roberts, Hannah Parraga, James Weng, Wenqian Xu, Uta Ruett, Alexander Hexemer, Petrus Zwart, Nickolas Schwarz

Scientific researchers frequently use the in situ synchrotron high-energy powder X-ray diffraction (XRD) technique to examine the crystallographic structures of materials in functional devices such as rechargeable battery materials.

Image Segmentation Semantic Segmentation +1

DLSIA: Deep Learning for Scientific Image Analysis

no code implementations • 2 Aug 2023 • Eric J Roberts, Tanny Chavez, Alexander Hexemer, Petrus H. Zwart

We introduce DLSIA (Deep Learning for Scientific Image Analysis), a Python-based machine learning library that empowers scientists and researchers across diverse scientific domains with a range of customizable convolutional neural network (CNN) architectures for a wide variety of tasks in image analysis to be used in downstream data processing, or for experiment-in-the-loop computing scenarios.

MLExchange: A web-based platform enabling exchangeable machine learning workflows for scientific studies

no code implementations • 20 Aug 2022 • Zhuowen Zhao, Tanny Chavez, Elizabeth A. Holman, Guanhua Hao, Adam Green, Harinarayan Krishnan, Dylan McReynolds, Ronald Pandolfi, Eric J. Roberts, Petrus H. Zwart, Howard Yanxon, Nicholas Schwarz, Subramanian Sankaranarayanan, Sergei V. Kalinin, Apurva Mehta, Stuart Campbell, Alexander Hexemer

Machine learning (ML) algorithms are showing a growing trend in helping the scientific communities across different disciplines and institutions to address large and diverse data problems.