Light-field Microscopy has emerged as a type of scanless, high-speed, 3D imaging tool. We propose model-based explainable deep learning approaches for LFM imaging, which integrates wave-optics theory, sparse representation and non-linear optimization with the artifcial neural network.
active 2024-04-19 → 2024-06-16 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 59 days from 2024-04-19 to 2024-06-16. Pushes: 2 total, peak 2 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 1 total, peak 1 in a day. Comments: 0 total, peak 0 in a day. Stars: 0 total, peak 0 in a day.
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Top contributors
Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity
| Contributor | Contributions | Pushes | PRs | Comments |
|---|---|---|---|---|
| Song-Pingfan | 2 | 2 | 0 | 0 |
| aldiak | 1 | 0 | 0 | 0 |
Recent activity
Latest issues, pull requests and releases
Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 0 stars here means stars gained during the window, not the repo's star count.