Result for 6152FBA6695A61A95E0162D3CE4D52CACDBE8966

Query result

Key Value
FileName./usr/lib/liblevmar.so.2.6
FileSize102236
MD5C2AED064FB4A48B091BF5AC3E19AB186
SHA-16152FBA6695A61A95E0162D3CE4D52CACDBE8966
SHA-256B4B0059A69FF9FCC797B6D09398945A9265C88FB7171D2D333354C16BAE95C6A
SSDEEP1536:8mG0p1UZExt7usrDy5Lyk2panFX+QqG9wLIp7niqSxmnaDOA:9p1UUkLyk2pandqG9o4DiqpZA
TLSHT177A3398ABC409FA1C8C0A6F4933E979833131BB1D3A771579016E7347BA65290F3BB49
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
MD5141D9D0C7F36FDB9F5DA5CDE7CD66C2F
PackageArcharmv7hl
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.
PackageMaintainerFedora Project
PackageNamelevmar
PackageRelease2.fc32
PackageVersion2.6
SHA-1D3C96CC786E3BFB862298D1CE7537359BC16CDA6
SHA-2568860E43400B1F000B1F0D2EE2F46FBA4B391EFE2CFF9D7B5D90074976AD689AF