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Deep Learning Computer Vision

ORAL · Q32 · ID: 48673






Presentations

  • A neural network can hear the shape of a drum

    ORAL

    Presenters

    • Yueqi Zhao

      UC San Diego, University of California, San Diego

    Authors

    • Yueqi Zhao

      UC San Diego, University of California, San Diego

    • Michael M Fogler

      University of California, San Diego

    View abstract →

  • Deepfake Video Detection Using Biologically Inspired Geometric Deep Learning

    ORAL

    Presenters

    • Jansen Wong

      Great Neck South High School

    Authors

    • Steven Luo

      Evergreen Valley High School

    • Jansen Wong

      Great Neck South High School

    • Yash Agarwal

      Dougherty Valley High School

    • Aayush Sheth

      Tesla STEM High School

    • Krish Jain

      Redmond High School

    • Eric Zhu

      Princeton High School

    • Eric Guan

      North Carolina School of Science and Mathematics

    • Nilesh Chaturvedi

      Department of Applied Mathematics and Statistics, Stony Brook University

    • Pawel Polak

      Department of Applied Mathematics and Statistics, Stony Brook University

    View abstract →

  • Unsupervised Machine Learning for Spatio-Temporal Characterization of Nanoscale Phenomena Imaged via Ultrafast Electron Microscopy

    ORAL

    Presenters

    • Thomas E Gage

      Argonne National Laboratory

    Authors

    • Faran Zhou

      Argonne National Laboratory

    • Thomas E Gage

      Argonne National Laboratory

    • Haihua Liu

      Argonne National Laboratory

    • Ilke Arslan

      Argonne National Laboratory

    • Haidan Wen

      Argonne National Laboratory

    • Maria K Chan

      Argonne National Laboratory

    View abstract →

  • Lithium Metal Battery Characterization using X-ray Imaging and Machine Learning

    ORAL

    Publication: [1] Noack, Zwart, Ushizima, Fukuto, Yager, Elbert, Murray, Stein, Doerk, Tsai, Li, Freychet, Zhernenkov, Holman, Lee, Chen, Rotenberg, Weber, Le Goc, Boehm, Steffens, Mutti, Sethian, "Gaussian Processes for Autonomous Data Acquisition at Large-Scale X-Ray and Neutron Scattering Facilities", Nature Reviews Physics, 2021.<br>[2] Ushizima, McCormick, Parkinson, "Accelerating Microstructural Analytics with Dask for Volumetric X-ray Imaging", PyHPC, 9th Workshop on Python for High-Performance and Scientific Computing, Supercomputing Nov 2020.<br>[3] Ushizima and Noack, Gaussian Processes and Deep Learning for Experimental Data, Machine Learning and Data in Polymer Physics II, APS March Meeting 2021.<br>[4] Siqueira, Ushizima, van der Walt, Large-scale segmentation using fully convolutional neural networks, https://arxiv.org/pdf/2101.04823.pdf.

    Presenters

    • Daniela Ushizima

      Lawrence Berkeley National Laboratory, UC Berkeley, UC San Francisco

    Authors

    • Daniela Ushizima

      Lawrence Berkeley National Laboratory, UC Berkeley, UC San Francisco

    • Ying Huang

      National Fuel Cell Research Center, UC Irvine

    • Jerome Quenum

      UC Berkeley, Lawrence Berkeley National Laboratory

    • David Perlmutter

      Lawrence Berkeley National Laboratory

    • Dilworth Parkinson

      Lawrence Berkeley National Laboratory

    • Iryna Zenyuk

      National Fuel Cell Research Center, UC Irvine

    View abstract →