libarmnntfliteparser24t64
Arm NN TensorFlow Lite parser library
Arm NN is a set of tools that enables machine learning workloads on
any hardware. It provides a bridge between existing neural network
frameworks and whatever hardware is available and supported. On arm
architectures (arm64 and armhf) it utilizes the Arm Compute Library
to target Cortex-A CPUs, Mali GPUs and Ethos NPUs as efficiently as
possible. On other architectures/hardware it falls back to unoptimised
functions.
libarpack2t64
Fortran77 subroutines to solve large scale eigenvalue problems
ARPACK software is capable of solving large scale symmetric,
nonsymmetric, and generalized eigenproblems from significant
application areas. The software is designed to compute a few (k)
eigenvalues with user specified features such as those of largest
real part or largest magnitude. Storage requirements are on the order
of n*k locations. No auxiliary storage is required. A set of Schur
basis vectors for the desired k-dimensional eigen-space is computed
which is numerically orthogonal to working precision. Numerically
accurate eigenvectors are available on request.
rtl-ais
simple AIS tuner and generic dual-frequency FM demodulator
This provides the rtl_ais command, which decodes AIS data from Software
Defined Radio (SDR) and outputs AIVDM / AIVDO sentences.
libatrilview3t64
MATE document viewing library
Atril is a simple multi-page document viewer. It can display
and print PostScript (PS), Encapsulated PostScript (EPS), DJVU, DVI, EPUB,
ComicBook and Portable Document Format (PDF) files.
python3-samsung-mdc
Samsung Multiple Display Control (CLI, Python 3)
Samsung-MDC is an implementation of the Samsung Multiple Display Control
Protocol using Python and asyncio.
libparpack2t64
Parallel subroutines to solve large scale eigenvalue problems
ARPACK software is capable of solving large scale symmetric,
nonsymmetric, and generalized eigenproblems from significant
application areas. The software is designed to compute a few (k)
eigenvalues with user specified features such as those of largest
real part or largest magnitude. Storage requirements are on the order
of n*k locations. No auxiliary storage is required. A set of Schur
basis vectors for the desired k-dimensional eigen-space is computed
which is numerically orthogonal to working precision. Numerically
accurate eigenvectors are available on request.