Result for 0082C65769DC448417FE396186A2A4360A90CB6D

Query result

Key Value
FileName./usr/lib64/liblevmar.so.2.6
FileSize200848
MD5ECD33B1FB54FFEA7F02C161DC97CA5C9
SHA-10082C65769DC448417FE396186A2A4360A90CB6D
SHA-256B0A9BDD72FCA53DD7EDC6D4211151C6AD649FB5B42704F29B781D75D020A4402
SSDEEP1536:0XwmBInXjocoGiNiKs5bp01cE04F7ebH4WVh6FObwGqhurLqKW6IlragQdZRcg:CIjVoGiNiKs5bp01cE02e0Ubqwd
TLSHT142146C2733486B05DBC06C7F834D6E61B7A6394B162895E3ED40831B6E75B3ACB47A4C
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
MD52D15257FBC356052C44599062442F852
PackageArchppc64le
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
PackageRelease3.el8
PackageVersion2.6
SHA-17F674ED65E63F7584F1BDA64C9386F6322B93BD7
SHA-25655F29B81C321387A2F8855A438F2EFF84D39EFF75430E6CAFEF0E8F834775D9E