https://github.com/3mcloud/afm-cbir-examples

Code to accompany Reverse AFM Height Map Search: Content-Based Topography Retrieval via Self-Supervised Deep Learning

https://github.com/3mcloud/afm-cbir-examples

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Code to accompany Reverse AFM Height Map Search: Content-Based Topography Retrieval via Self-Supervised Deep Learning

Basic Info
  • Host: GitHub
  • Owner: 3mcloud
  • License: mit
  • Language: Jupyter Notebook
  • Default Branch: main
  • Size: 1.74 MB
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Created over 1 year ago · Last pushed over 1 year ago
Metadata Files
Readme License

README.md

Reverse AFM Height Map Search: Content-Based Topography Retrieval via Self-Supervised Deep Learning

By Marcus Schwarting, Matthew JL Mills, Mahsa Lotfollahi, Maryam Pardakhti, KJ Schmidt, Bahram Rajabifar, Bjorn Melin, Hyacinth Lechuga, Ben Blaiszik and Ian Foster

This repository contains example data and code demonstrating how to reproduce the data pre-processing and model building procedures defined in the above paper. All code need for loading, reading, and performing model inference on AFM topographies is provided in this repository. Any questions can be referred to Marcus Schwarting (meschw04@uchicago.edu).

For more information, please check out our paper in Springer "Integrating Materials and Manufacturing Innovation".

Owner

  • Name: 3M
  • Login: 3mcloud
  • Kind: organization
  • Location: Maplewood, MN

Science. Applied to life.

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Dependencies

requirements.txt pypi