Result for D41607E7DAD72A9F93461114E98B8E15A1731C31

Query result

Key Value
FileName./usr/lib64/liblevmar.so.2.6
FileSize123536
MD5625E10CD3D79A6E089EF5C401E2798BA
SHA-1D41607E7DAD72A9F93461114E98B8E15A1731C31
SHA-2564AB6B70B35C3EE568F5B707EE073D2875B995135971B896CEDEF028EF0308B16
SSDEEP3072:z2uM0AEbw5ofiHEdqW06XQJCUpDKg/sfliDUsl5N:quvAmw5oqHELMD3sfliQsl5N
TLSHT144C34A87F2B35868C0D1C474A269B117B6317409653DBA3B5B80D2702E7FF192EAFB64
hashlookup:parent-total1
hashlookup:trust55

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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
MD56A0B2A54CCF5EDD4FC4D32CE1E300AF1
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
PackageRelease3.el8
PackageVersion2.6
SHA-1B03515D6735EDE3545CE811BBCE412E2BFF87C9C
SHA-256E6C2D0BE9A7730FD16611FB15F4F4EF7C3354AE35D4A50B44BD4003F988E9E08