Key | Value |
---|---|
FileName | ./usr/lib/liblevmar.so.2.2 |
FileSize | 194080 |
MD5 | 2C8D16BDF7862209554D8B059C7F371A |
SHA-1 | 8CC902BF74CB04D50118D7F97BE1EB03022CB4D1 |
SHA-256 | 606468144728C740EE91699D944F38D7FCB83F8835348D88CB0FCC3FA0862A64 |
SSDEEP | 3072:50zVJdqqFQlUpsnhnnnwFrQeVTV9poVi49B685qrGFrvk84sFsjmamPVcvn/nnYj:azVJdqqulUpsnhnnnwFceJik4350ervv |
TLSH | T134146CD2BD520C50C9C1D3F3923FCB15B38746B5E37A7143461097A832A7A1AAF7B686 |
hashlookup:parent-total | 1 |
hashlookup:trust | 55 |
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 |
---|---|
MD5 | 9858C1342DFD50547A85B1EEEE868CD3 |
PackageArch | armv7hl |
PackageDescription | levmar 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. |
PackageMaintainer | umeabot <umeabot> |
PackageName | liblevmar2 |
PackageRelease | 2.mga7 |
PackageVersion | 2.6 |
SHA-1 | 544B8C9F54ACFCC9E34770DC90C74B5B48F7A1F1 |
SHA-256 | 964F99F69FBC9E5FB3659E768AEB5F56F1D34ADD7A7CAF4BD79D0535E54DBF24 |