https://github.com/centre-for-humanities-computing/mounddetection
Analysis of IKONOS satellite imagery for the Tundzha Regional Archaeological Project
https://github.com/centre-for-humanities-computing/mounddetection
Last synced: 10 months ago
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Analysis of IKONOS satellite imagery for the Tundzha Regional Archaeological Project
- Host: GitHub
- URL: https://github.com/centre-for-humanities-computing/mounddetection
- Owner: centre-for-humanities-computing
- License: mit
- Created: 2021-08-19T05:46:49.000Z (almost 5 years ago)
- Default Branch: main
- Last Pushed: 2021-08-19T06:31:06.000Z (almost 5 years ago)
- Last Synced: 2025-02-22T22:41:46.933Z (over 1 year ago)
- Language: Jupyter Notebook
- Size: 513 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Analysis of IKONOS satellite imagery for the Tundzha Regional Archaeological Project
The goal of this project is to build a machine learning system that
can identify potential burrial mounds in satellite images to a high
degree of accuracy. In this repository we are investigating two
avenues: classification of multi-band postage-stamp image centred on
burrial mounds and segmentation of large images to highlight burrial
mounds and other relevant features.
## Environment Setup
For GIS tasks remember to activate the GIS python environment. See
[HERE](https://github.com/crpurcell/IntroPythonGIS).
For ML tasks activate the DL4CV environment using ```workon dl4cv```.