Result for 7A31B2280F471D26B24DFF7D5A996C7900BFACAA

Query result

Key Value
FileName./usr/lib64/liblevmar.so.2.6
FileSize127664
MD514E1B425804CB601949DFDBB74519089
SHA-17A31B2280F471D26B24DFF7D5A996C7900BFACAA
SHA-25683743B4E889F1D0063050C969CAB49CB776EB1CF2018D438C9AA736D739D9216
SSDEEP3072:x2OMLvrn88j39HVo3uBo5atJZOPa0AjeykMxW0Y7kTVK2/6:xBM38879W6o5atJ4Pa0A7kMxW0Y7kR/6
TLSHT163C32887F2A218B8C4E19430A65AB213B7303448A53C77776BC0D6701DBBF257EAB765
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
MD51AC7399E6D3B1C54425D9FA3427C1E07
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.
PackageMaintainerFedora Project
PackageNamelevmar
PackageRelease2.fc32
PackageVersion2.6
SHA-148F0DA86586705020138224CED7F532EF6A3F644
SHA-25695FFB8DCE30D0086A7178058CC7A2BD0E1DDC75FED7D6D3871264D3F6FE23807