Result for 6FD38C169BE3A6AAF0E7DFD3B57E2F4B38C1BEC1

Query result

Key Value
FileName./usr/lib64/liblevmar.so.2.2
FileSize208992
MD507E22334D58C0248DE3D7A180706C827
SHA-16FD38C169BE3A6AAF0E7DFD3B57E2F4B38C1BEC1
SHA-2566274ADE2EA1F3412DD2D802AA81DC571E7F744781D989D59434AB2153CC73C04
SSDEEP6144:vogZANNrBUU6T7g5xa4Vr5yW7TW+5DpTHO:CrL6AZPx0
TLSHT1E3149E1AE60EFE6AC0C1F7B1DD5E4D4C7309248A8323719EE600C3F67696AB466F4B15
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
MD5FF5FC1FC185619BA42D2380B830E0F04
PackageArchaarch64
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.
PackageMaintainerumeabot <umeabot>
PackageNamelib64levmar2
PackageRelease3.mga8
PackageVersion2.6
SHA-1941BD2ECCBAED0ACE4FBC99B24E3919C00609CF2
SHA-2567C38653C140A64DFF41E1DD38AB209E5CC891152456067375F9B76505A3B3113