Result for 70F0CFFE6AEEF16086FB4F0348442FC8D75F632F

Query result

Key Value
FileName./usr/lib/liblevmar.so.2.6
FileSize101952
MD5E3DAEB8192F686B87CE35EF43424128A
SHA-170F0CFFE6AEEF16086FB4F0348442FC8D75F632F
SHA-256B5FED9CCBD68FB4D75584440CBEF2209D4891116D6C4307D8ACDDEDD2DA1B1ED
SSDEEP1536:3Cy0Sjm9FBLpV7l2Ycg6vES6fSejgB1kZUc1Z3mnaDOt:xkFB77t6vESoUc1ZUZ
TLSHT183A32A8ABC419FA1C8C0A2B5937D879833131BB1E3A772479415E7346B9A52D0F3BF49
hashlookup:parent-total1
hashlookup:trust55

Network graph view

Parents (Total: 1)

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
MD5DBA9E1E2326C4BCF4E39D8559C572348
PackageArcharmv7hl
PackageDescriptionlevmar 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.
PackageMaintainerFedora Project
PackageNamelevmar
PackageRelease7.fc34
PackageVersion2.6
SHA-1E9AE365C4EA8629F6DDBDA21C143C2D58FA9D877
SHA-2568F7FDDA57FABAD5B73DFF0D73FA5774C309748C84C691B44554FE59AB71D785C