BIDS hosted the third annual ImageXD Workshop on May 16–18. ImageXD (Image Processing Across Domains) bringing together researchers from a variety of fields, who share an interest in applications of, as well as algorithms and software for, image analysis.
Date/Time: May 16-18, 2018, 9:00 AM - 5:00 PM
Location: Berkeley Institute for Data Science, 190 Doe Library, UC Berkeley
Registration is now closed; this event has reached full capacity.
Program - This three-day event featured tutorials, talks, and collaborative work sessions:
- Tutorials on image processing software tools such as NumPy, SciPy, scikit-image, Keras, TensorFlow, and Dask.
- Presentations and lunchtime panels about algorithms & solutions utilized by practitioners in fields other than your own.
- Collaborative work sessions with time to build software, explore new methods, develop educational material, or solve an existing research problem with a technique from another domain.
Maxim Ziatdinov — Oak Ridge National Laboratory
Deep learning for atomically resolved imaging techniques: chemical identification and tracking local transformations
James Coughlan — Smith-Kettlewell Eye Research Institute
Computer vision for the visually impaired
Amit Kapadia — Planet Labs
Building Global Mosaics
Natalie Larson — UC Santa Barbara
In-situ X-ray computed tomography for defect evolution
John Canny — UC Berkeley
Deep net visualization, interpretable driving
John Kirkham — Howard Hughes Medical Institute
Interactively analyzing larger than memory neural imaging data
Matt McCormick — Kitware, Inc.
Interactive Analysis and Visualization of Large Images in the Web Browser
Suhas Somnath — Oak Ridge National Laboratory
Pycroscopy - a python package for analyzing, storing, and visualizing multidimensional scientific imaging data
James Sethian — CAMERA, Lawrence Berkeley National Laboratory
Mathematics for image across domains
Deep Ganguli — Chan Zuckerberg Initiative
Starfish: A Python library for Image Based Transcriptomics
2018 ImageXD Workshop– using images to cross science boundaries and domains
May 22, 2018 | Daniela Ushizima | BIDS Blog: Data Science Insights
Dani Ushizima leads the Image Processing team for the Center of Advanced Mathematics for Energy Research Applications (CAMERA) in the Computational Research Division at Lawrence Berkeley National Lab. She is also the Principal Investigator of the U.S. Department of Energy Early Career Research Project called Image across Domains, Algorithms and Learning (IDEAL). Her interests include pattern recognition, computer vision, machine learning, signal processing, quantitative microscopy, and microstructure inspection in materials sciences .