Key | Value |
---|---|
FileName | ./usr/lib/liblevmar.so.2.2 |
FileSize | 191688 |
MD5 | 33C8B9040D9D030A23343E5D3F126282 |
SHA-1 | C5E1A1EBB808F92416663E96E914F327773D074C |
SHA-256 | 8BE386942611A016F5C10BB337EC60F38764D16B66BF8EBC713C8EC7A7D89647 |
SSDEEP | 3072:hR6QRxs+LvUnLnnnnJW4bKHFEj0eqmILCvPjBTzMGJuHaSf6Vsv9YZ:36kxsqvUnLnnnneqIWvPNTzf8esv9YZ |
TLSH | T175147D91BD521C51C8C1D3F3E23FCB55B38646F9E37A3452460093A835ABA26EF7B246 |
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 | 4DF1137B2DE810F131FBE45C732A958F |
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 | 3.mga8 |
PackageVersion | 2.6 |
SHA-1 | 2C516AD80F00064180E1FB0280404DCCC1873D00 |
SHA-256 | 26AAB990F14537FB4CA2F2D0AEDAD10F4517FBF002960D2B29D7EF8BA3172ADB |