| Key | Value |
|---|---|
| FileName | ./usr/lib64/liblevmar.so.2.6 |
| FileSize | 135984 |
| MD5 | EB8F7D50A70DDFBE63BCE1D6B3B31709 |
| SHA-1 | D54B4D3750A75EA7A450B9F95A9839CD5945CBCF |
| SHA-256 | 0341EDE2F97140A05E2AA093565A9805E2564CF33BD16AE76FA64439EF70A118 |
| SSDEEP | 1536:P5ACIHusqE0bqUv2KvB5WnqPlNJweonX9LkioEh4LwI0F/xn4xLKKW6J6eZf4:XIZqhbqUVvB5WqNunX63EMwHhhz |
| TLSH | T133D36D1DBE1F7802C1C1B37963594A5C733F2294F35660F32046C3EC6B06EAA9BA7655 |
| hashlookup:parent-total | 1 |
| hashlookup:trust | 55 |
The searched file hash is included in 1 parent files which include package known and seen by metalookup. A sample is included below:
| Key | Value |
|---|---|
| MD5 | D97323DAD70DFB690F19E52C0A3A3A3D |
| PackageArch | aarch64 |
| PackageDescription | levmar is a native ANSI C implementation of the Levenberg-Marquardt optimization algorithm. Both unconstrained and constrained (under linear equations, inequality and box constraints) Levenberg-Marquardt variants are included. The LM algorithm is an iterative technique that finds a local minimum of a function that is expressed as the sum of squares of nonlinear functions. It has become a standard technique for nonlinear least-squares problems and can be thought of as a combination of steepest descent and the Gauss-Newton method. When the current solution is far from the correct on, the algorithm behaves like a steepest descent method: slow, but guaranteed to converge. When the current solution is close to the correct solution, it becomes a Gauss-Newton method. |
| PackageMaintainer | Fedora Project |
| PackageName | levmar |
| PackageRelease | 7.fc34 |
| PackageVersion | 2.6 |
| SHA-1 | 38C2A4DD63C49EDE6BB3DC61F2684652F81AF616 |
| SHA-256 | CBCAAD4AD0B774E5278055BA9D50F0617F9E4CEB426008129C52B6337F42EDA0 |