mikebianco/locally-sparse-tomography

Locally sparse travel time tomography (LST) is a tomography algorithm which uses sparse modeling and dictionary learning to estimate 2D geophysical images based on wave travel times across sensor arrays. This repository is an implementation of the IEEE paper: M.J. Bianco and P. Gerstoft, "Travel time tomography with adaptive dictionaries," IEEE Trans. on Computational Imaging, Vol. 4, No. 4, 2018.

16
Stars
10
Forks
0.0
Radar Score
Declining
Momentum

Scoring Breakdown

Impact0.0
Velocity0.0
Health0.0

Growth Metrics

7-Day Stars
+0
30-Day Stars
+0
Acceleration
x
Language
MATLAB

Why it ranks

Momentum is cooling relative to the rest of the index.

Local AI · local runner

🛡️ Enterprise Readiness & Commercial Safety

Organic Growth
95%
High Confidence
Growth pattern looks organic.
License
Unlicensed / Custom
Review license terms carefully before commercial adoption.
Health Grade
C
Based on maintenance, issue response, and release cadence.
Radar Score
0.0
Composite of Impact, Velocity, and Health.
Disclaimer: This is an automated heuristic assessment based on public GitHub signals. Always perform your own security audit, dependency review, and legal compliance check before production deployment.

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