Result for 8B4AE6CBC211971F1F96F5A6C57C7ADA8AA5F840

Query result

Key Value
FileName./usr/lib64/liblevmar.so.2
FileSize124808
MD588D6D52D947F8D14B59C50BE5AF9B2FD
SHA-18B4AE6CBC211971F1F96F5A6C57C7ADA8AA5F840
SHA-2560E850EA52B3A13ED6B80AB076AA9D9660D83BC2F431C4C9B4FD6CFC86F99B1E1
SSDEEP3072:ErU7OmbAh1PoB9XmEWJ67Oei48IwMmeyCBBr:vimgCZd7a48IbnNBr
TLSHT171C32ACBB9A187A7C0B02D77C35E67F6531729393AC67D2EA7A9D7300C13510AB06B52
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
MD535772295A30AF340465E97DFA2BD1DA3
PackageArchs390x
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
PackageMaintainerhttps://bugs.opensuse.org
PackageNameliblevmar2
PackageReleasebp156.2.6
PackageVersion2.6
SHA-100C6AFE5A7AAB8D27BD62212A48F319D3C4EE7B4
SHA-256A85E5A45764761B0A10FCEE1A4BA052AC97E93BB1CFA00312E32ACCC447E5FC8