Result for AEDA526138F3FC5B4189A3BDD1BF37EC5C56B876

Query result

Key Value
FileName./usr/lib64/liblevmar.so.2.6
FileSize127560
MD5267E0FEEB38278BF064AD2812EECB1F2
SHA-1AEDA526138F3FC5B4189A3BDD1BF37EC5C56B876
SHA-256956D79AC6521020B1FCCBD0CA50C2784111D76DA134D9B59286AB6290344FEF1
SSDEEP3072:KTfwr1QT5pO0q9EiVE4YsQrc/aZMCVmOkZi7cPU1v7+Pd7G8:QE45k08VZ1QrcSZMCVmOUi7cPU1v7+P3
TLSHT14DC34A83F3A218B4C0E19574A65AF207BA703449A62CBB7767C0D6301E7BF143E9B765
hashlookup:parent-total1
hashlookup:trust55

Network graph view

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
MD55FCED4467A4061B22D44CC679BE72614
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
PackageRelease6.fc33
PackageVersion2.6
SHA-1DFFF4322CBD0243471C0776527BFA3A94BBE6586
SHA-2564CF6267B785F15FD4D858F857FF08BC0F097B615E77207A349A1C23AA66DFA46