Result for A64A1F7C83B2899B9E229BC73ECC940F33A26669

Query result

Key Value
FileName./usr/lib64/liblevmar.so.2.2
FileSize248344
MD50BF299A8763ABCC760D0D0DB9314C377
SHA-1A64A1F7C83B2899B9E229BC73ECC940F33A26669
SHA-25682487AE83B60717158D60436D03CE1A1AF4C0D603B808663766B215DA6E741B9
SSDEEP6144:Na9gNuOrvpaEDh0Snhw1aKqoioqFkwGWTqj1iw6:uyu0B1DhnhIzUGWTqjM
TLSHT1F7344C46718118FCD1E67576A2FAB41B323330195719AEF613D24B702E2AD122F93B6F
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
MD5C63A57F66D8012F6585F4D6D28F2E753
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.
PackageMaintainerumeabot <umeabot>
PackageNamelib64levmar2
PackageRelease2.mga7
PackageVersion2.6
SHA-1ADE0C6F0F0D8CD050CA03BFDCBDBB4A4D2BF7F16
SHA-2561246F8F2DAE7E216186A4C511EEB4B9D7D02B9F4D852F1BB9C4CF114662AF298