Search Results for "accurate"

Build always-listening yet private voice applications. Porcupine is a highly-accurate and lightweight wake word engine. It enables building always-listening voice-enabled applications. It is using deep neural networks trained in real-world environments. Compact and computationally-efficient. It is perfect for IoT. Cross-platform. Arm Cortex-M, STM32, PSoC, Arduino, and i.MX RT. Raspberry Pi, NVIDIA Jetson Nano, and BeagleBone.

...⚠️ Note on Virtual Machines: NebiOS X is optimized and designed for real hardware performance and native GPU acceleration. Virtualization platforms (VMware, VirtualBox, GNOME Boxes, etc.) may show degraded graphics or system performance. For accurate testing, please install NebiOS X on physical hardware. === System Requirements and informations about before installation can be found at https://nebios.org/download (select your version for it)

...The minimum viable computer to run our localization and SLAM solutions is a Raspberry Pi 3 Model B+. We provide a fast scan-matching approach to mobile robot localization supported by a continuous likelihood field. It can be used to provide accurate localization for robots equipped with a laser and a not-so-good odometry. Nevertheless, good odometry is always recommended.

...The absence of large datasets of ‘with_mask’ images has made this task cumbersome and challenging. Our face mask detector doesn't use any morphed masked images dataset and the model is accurate. Owing to the use of MobileNetV2 architecture, it is computationally efficient, thus making it easier to deploy the model to embedded systems (Raspberry Pi, Google Coral, etc.).

...It allows you to recognize and manipulate faces from Python or from the command line using dlib's (a C++ toolkit containing machine learning algorithms and tools) state-of-the-art face recognition built with deep learning. Face Recognition is highly accurate and is able to do a number of things. It can find faces in pictures, manipulate facial features in pictures, identify faces in pictures, and do face recognition on a folder of images from the command line. It could even do real-time face recognition and blur faces on videos when used with other Python libraries.

The goal of the Perl OBD-II Logger project is to create a flexible and efficient application that can capture and log OBD-II Mode 0x01 PID data from an automotive scantool. It is designed with accurate and efficient PID data logging in mind, and provides NO support for reading or resetting diagnostic trouble codes. By default, the output log file contains time-stamped PID values in a simple Comma Separated Values (CSV) format that can be readily imported into popular data analysis or spreadsheet applications. (Output to an SQLite3 database file is also available). ...

...This is an old version of SNES9X but was chosen as it runs mostly at full speed on the Raspberry Pi unlike the more recent versions of SNES9X. Game support is therefore not as good as the newer SNES9X versions and graphics & sound is not as accurate. Games that will not work, for example, are Yoshi's Island, Street Fighter Alpha 2, Star Fox. This port supports keyboard and USB joystick input and are configurable. It uses GLES2/dispmanx for graphics so can run equally well in the Console or under X-Windows. The audio uses the ALSA API and SDL is used for input. Source code has moved to github https://github.com/squidrpi/pisnes