chanformer
Datasets and codes for "Learning to Localize with Attention: from sparse mmWave channel estimates from a single BS to high accuracy 3D location".
Science Score: 26.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
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○Academic publication links
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○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (2.3%) to scientific vocabulary
Last synced: 10 months ago
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JSON representation
Repository
Datasets and codes for "Learning to Localize with Attention: from sparse mmWave channel estimates from a single BS to high accuracy 3D location".
Basic Info
- Host: GitHub
- Owner: WiSeCom-Lab
- License: mit
- Language: Python
- Default Branch: main
- Size: 5.59 MB
Statistics
- Stars: 2
- Watchers: 0
- Forks: 0
- Open Issues: 0
- Releases: 0
Created over 2 years ago
· Last pushed almost 2 years ago
Metadata Files
Readme
License
Citation
README.md
ChanFormer
Datasets and codes for "Learning to Localize with Attention: from sparse mmWave channel estimates from a single BS to high accuracy 3D location".
Install required packages
Check and install the required packages: pip install -r requirements.txt.
Load Dataset
Owner
- Name: WiSeCom-Lab
- Login: WiSeCom-Lab
- Kind: organization
- Repositories: 4
- Profile: https://github.com/WiSeCom-Lab
GitHub Events
Total
- Watch event: 1
Last Year
- Watch event: 1
Dependencies
requirements.txt
pypi
- matplotlib *
- tensorflow *