Key | Value |
---|---|
FileName | ./usr/lib/liblevmar.so.2.6 |
FileSize | 101856 |
MD5 | 729824048EC17AD0AF90D6C93F1C7538 |
SHA-1 | 21C897A6904DC0E66D8DA6048F8340FF0794FD97 |
SHA-256 | 3AD110F6483078EEFA25721203411A344C2A9DFB864924DAF7EDEC625BC59284 |
SSDEEP | 1536:E9JQft01BD7yDl6GQscwa7AJ9Ar6qQr/+xL+sNDsHO8nXrLemnaDO:1t01BD7O0scwa7AJXqQr/+d/OXrLXZ |
TLSH | T15AA33A8ABC419FA1C8C092F5933D979833031BB1D3A772579416E7346B9A52E0F3BB49 |
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 | 05BE1DE5F8692F11CE13E61F137EE5A2 |
PackageArch | armv7hl |
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 | 6.fc33 |
PackageVersion | 2.6 |
SHA-1 | 03C32B473726C70220E95B5855336F6113292815 |
SHA-256 | 91264CB306509A3ECA0D1215702B07A4528131EA7A7949FC6A323CD3F79A6DFD |