Result for 672B8ED1A747550399C12F0F7A3A7B3C8386D527

Query result

Key Value
FileName./usr/lib64/liblevmar.so.2.2
FileSize207328
MD5F4E7ECF1566179C03AFFDFD3D8AB1FAE
SHA-1672B8ED1A747550399C12F0F7A3A7B3C8386D527
SHA-2562C831E444A201C760265A8FF3E9149F33365B63DBEC9661443AD51D388CF584A
SSDEEP6144:h4Db3N6liRZdbMGG+3a7I8S1Q3FLuGvhnMLqXUeUM:iDbd6YVjXb1YhI4UM
TLSHT138149E59EA1AEE27C5C4F736ED9A0E9D3704248A9333718B9000C6F67242BF166F5F19
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
MD5E940A63C7329BD0565578AF6DE5DDAAC
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
PackageRelease2.mga7
PackageVersion2.6
SHA-1086AC87C37AD753A705CDE221A87AF21C31C78DE
SHA-256785A451B9681AE2A46FF9DBDD1D9E5D492CA6403C18432589684A1D63C6B3491