Result for 85F8770A759E800CB4CB3626A32FFFF0CF7EDE42

Query result

Key Value
FileName./usr/lib/liblevmar.so.2.2
FileSize218752
MD504AA62D73F50D9E3A9F611BAD2499EB7
SHA-185F8770A759E800CB4CB3626A32FFFF0CF7EDE42
SHA-25693736ABAC713527F5D3A66D8573B74E8A5666291EC77D0BEC0BD77D8E779C6F8
SSDEEP6144:woQxvUPToPPPPup2jcqsOM1B2klYA4fj3uu:nQtUPToPPPPSSY2kqfj3uu
TLSHT161246C86E7C64198D0D31CB195A7E73BF6249F452123F7F4ABDEAB01A934B1B3D28244
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
MD5AA46846E9C7C7C20BB5758E34346AB95
PackageArchi586
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>
PackageNameliblevmar2
PackageRelease2.mga7
PackageVersion2.6
SHA-17E2F2C667B9FA5EB68DDE492DCB98379B3C38130
SHA-256F06120634A1754160E14C804819A5C73C91FC1FE50D4ED2DD325FE478794A0C7