Optical Imaging of Ultrafast Photo-Induced Phase Transitions of Nanostructures Using Neural Lenses

Abstract

Under this Short-Term Innovative Research (STIR) Project, we have made a range of progresses on our project on Machine Learning for dynamic surface structural reconstruction. Our main goal was to demonstrate machine learning's ability to recover images from optical degradation. We used Neural Networks (NNs) to apply image super-resolution to the images obtained using ultrafast time-resolved scattered-light microscopy techniques.

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Document Details

Document Type
Technical Report
Publication Date
Aug 09, 2021
Accession Number
AD1209124

Entities

Organizations

  • University of Rochester

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Ablation
  • Algorithms
  • Contrast
  • Femtosecond Lasers
  • Femtosecond Time
  • Films
  • Frequency
  • Generators
  • Laser Beams
  • Lasers
  • Learning
  • Light Sources
  • Machine Learning
  • Microscopy
  • Neural Networks
  • Optical Coatings
  • Optical Modulators
  • Optics
  • Phase Transformations
  • Reliability
  • Solar Spectrum
  • Students
  • Training

Fields of Study

  • Physics

Readers

  • Computer Vision.
  • Neural Network Machine Learning.
  • Quantum Dot Semiconductor Device Photonics and Graphene Optoelectronic Materials and THz Physics.

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks
  • Microelectronics