Key | Value |
---|---|
FileName | ./usr/lib64/liblevmar.so.2 |
FileSize | 16 |
MD5 | 7DC64EDDC0D1DBF22BB7253CCD0232E0 |
SHA-1 | 516473F0BF017DA89C732C9A625EA22AE61B1CC9 |
SHA-256 | CD70106BD512A2DB657EC0527E93B7A063BCF53B7FB6E134849B7ED88A95ED62 |
SSDEEP | 3:EJO:Es |
TLSH | |
hashlookup:parent-total | 56 |
hashlookup:trust | 100 |
The searched file hash is included in 56 parent files which include package known and seen by metalookup. A sample is included below:
Key | Value |
---|---|
MD5 | 34CE3BE1472FA1592D194B6DBAB82AB9 |
PackageArch | i686 |
PackageDescription | Development files for the levmar library, and demo program. |
PackageMaintainer | Fedora Project |
PackageName | levmar-devel |
PackageRelease | 6.fc33 |
PackageVersion | 2.6 |
SHA-1 | 015A5274488599FC599B1CF8FA4218730F42323F |
SHA-256 | 168014030511345745F0D9DFFFBAE3C28DF460A78356543171DAD95783D4749F |
Key | Value |
---|---|
MD5 | 05BE1DE5F8692F11CE13E61F137EE5A2 |
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 | Fedora Project |
PackageName | levmar |
PackageRelease | 6.fc33 |
PackageVersion | 2.6 |
SHA-1 | 03C32B473726C70220E95B5855336F6113292815 |
SHA-256 | 91264CB306509A3ECA0D1215702B07A4528131EA7A7949FC6A323CD3F79A6DFD |
Key | Value |
---|---|
MD5 | 5347F1E6512760C9B9C7C20F5648B01D |
PackageArch | x86_64 |
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 | Fedora Project |
PackageName | levmar |
PackageRelease | 3.epel8.playground |
PackageVersion | 2.6 |
SHA-1 | 0DA574132C6B879C3CE78C2697970A5B4A6CD034 |
SHA-256 | 81287E07BB1A1212D99516701F5CFA026DF7FA5855A60D10567A7789131192FA |
Key | Value |
---|---|
MD5 | 3A383E422AE85D8B8506FFE5C0E2069D |
PackageArch | i586 |
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 | https://bugs.opensuse.org |
PackageName | liblevmar2 |
PackageRelease | 1.7 |
PackageVersion | 2.6 |
SHA-1 | 1090DF3997BFEF4735C4D5D831045B72A08FE43B |
SHA-256 | 4E883602424EECB0BC9F8C80712D0265D11867FF8CB0AB19BDD710D228FA8F0A |
Key | Value |
---|---|
MD5 | A2F8E3817A65D5C9D375B4433AD41FD2 |
PackageArch | ppc64le |
PackageDescription | Development files for the levmar library, and demo program. |
PackageMaintainer | Fedora Project |
PackageName | levmar-devel |
PackageRelease | 1.el7 |
PackageVersion | 2.6 |
SHA-1 | 109CC9EC633F1834944BD2C9CFDEB9A7AFA5CD55 |
SHA-256 | 3015FA3DD5225AD97A09C93DBBBEF99F99F40726BA0693CF8CF65D01F054566B |
Key | Value |
---|---|
MD5 | 4FFA1212DEAD06EFDC4A6A695526277C |
PackageArch | x86_64 |
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 | Fedora Project |
PackageName | levmar |
PackageRelease | 7.fc34 |
PackageVersion | 2.6 |
SHA-1 | 13F89F5D085B41A28ABBF6F1A96A08E4DFC041B3 |
SHA-256 | 1A0016DA47BD6B468FA5BEBB62FC40EB9C80F59CF0746D865A45AD4B06BA059F |
Key | Value |
---|---|
MD5 | 6D6CEDEF69D605CC9366912A10C4F6B7 |
PackageArch | i586 |
PackageDescription | Development files for the levmar library, and demo program. |
PackageMaintainer | https://bugs.opensuse.org |
PackageName | levmar-devel |
PackageRelease | 1.7 |
PackageVersion | 2.6 |
SHA-1 | 14782126D875BB36F53DAE35C07AB40D51E98D0E |
SHA-256 | A29E5B839E66EBD242EBD5A8B171E4A00CF61FF0F04EB659668002E34065CE71 |
Key | Value |
---|---|
MD5 | 3D8C64FF97D0C05799EA2AA5317597CD |
PackageArch | x86_64 |
PackageDescription | Development files for the levmar library, and demo program. |
PackageMaintainer | Fedora Project |
PackageName | levmar-devel |
PackageRelease | 3.epel8.playground |
PackageVersion | 2.6 |
SHA-1 | 17330B257DD3E6196C0E21A6577D54343C0E5292 |
SHA-256 | 048EFA3653B19E4625CC3E08B886CFED486AC804A6B2A8C59598DAED7AC3CA27 |
Key | Value |
---|---|
MD5 | 074277ADF1DBA510F05CC2240F7DC566 |
PackageArch | x86_64 |
PackageDescription | Development files for the levmar library, and demo program. |
PackageName | levmar-devel |
PackageRelease | lp150.6.1 |
PackageVersion | 2.6 |
SHA-1 | 1EC7EB973AD39337E5F6F147F17059E5E9D740AE |
SHA-256 | AB089FD5DC175F18A17829028914DB9A56E7D2E923F4F0B9B5962BFA948A367D |
Key | Value |
---|---|
MD5 | 81CE1EFF58757A9AF5CF7E3C37318C84 |
PackageArch | s390x |
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 | Fedora Project |
PackageName | levmar |
PackageRelease | 3.el8 |
PackageVersion | 2.6 |
SHA-1 | 33FBCA39106B6199A7E20D215B7EEC01670B1E98 |
SHA-256 | EBD94F0AE293B2E626FFE55DB804071CD0B6FD9534E07CE019FCCF7937F437E4 |