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

Last synced: 3 months ago
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Code to accompany Reverse AFM Height Map Search: Content-Based Topography Retrieval via Self-Supervised Deep Learning

• Host: GitHub
• URL: https://github.com/3mcloud/afm-cbir-examples
• Owner: 3mcloud
• License: mit
• Created: 2024-10-16T21:05:48.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-11-14T23:55:31.000Z (over 1 year ago)
• Last Synced: 2026-03-08T18:25:52.399Z (3 months ago)
• Language: Jupyter Notebook
• Size: 1.98 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# 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".