Result for 4C6FE37862C26C3C2A8F914669231170144271F5

Query result

Key Value
FileName./usr/lib64/liblevmar.so.2.6
FileSize127768
MD5DBE19AE8CA621FAD5761A602FC088FBC
SHA-14C6FE37862C26C3C2A8F914669231170144271F5
SHA-256D3C02FA29374EB6A2C59A9A362FA2190B401783090E5B3C4FA15C0F63937D1AA
SSDEEP3072:XrM32rKYo7fwYCoF/mnZGi4/Ped8BU7bYpYBZlOlMX:7MmZo7uopmnZzSw8BU7bY2BZN
TLSHT181C3294BE2A348B8C4D1D430A65AF213B6307459AA3C77775BC0D6301DBAF243EAB765
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
MD54FFA1212DEAD06EFDC4A6A695526277C
PackageArchx86_64
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-113F89F5D085B41A28ABBF6F1A96A08E4DFC041B3
SHA-2561A0016DA47BD6B468FA5BEBB62FC40EB9C80F59CF0746D865A45AD4B06BA059F