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Autoware is a modular autonomous driving stack and open-source platform for advanced driver assistance systems. It functions as an integrated operating environment that manages the full pipeline from sensor data processing to vehicle actuation, utilizing the ROS 2 robotics framework for distributed communication and hardware abstraction. The system provides a comprehensive software architecture to enable autonomous driving across various vehicle platforms. It coordinates perception, planning, and control systems to operate vehicles without human intervention. The platform covers several core
Deeplearning4j is a JVM-based deep learning framework and tensor computing library. It provides a computational graph engine for defining and executing deep learning workflows and mathematical operations within the Java Virtual Machine. The project includes a dedicated importer for loading and running pretrained models exported from Keras, TensorFlow, and ONNX formats. Its tensor computing capabilities are driven by a modular native C++ math core to execute high-performance linear algebra operations. The framework covers neural network training, deep learning model inference, and the constru
Neural Networks Demystified is an educational resource consisting of interactive Python notebooks designed to explain the fundamental mathematical concepts behind neural networks. It serves as a tutorial for understanding how these models process data and learn from patterns through supervised learning implementations. The project functions as a visualization tool that demonstrates core mechanics such as forward propagation and gradient descent. By utilizing notebook-driven execution, it allows for the inspection of intermediate data states and mathematical transformations as they occur durin
Apollo is a comprehensive software stack designed for autonomous vehicle development, providing the necessary components for perception, planning, and control. It functions as a high-performance robotics middleware, utilizing a publish-subscribe data bus to facilitate low-latency communication between distributed modules and hardware sensors. The platform integrates data from cameras, lidar, and radar through a sensor fusion framework to generate a real-time environmental model for navigation. The system features a component-based runtime framework that manages task scheduling and resource al
Racer is a self-driving remote-controlled car platform that integrates hardware schematics, an autonomous vehicle training framework, and a machine learning control system. It provides the necessary tools to build, train, and operate autonomous vehicles.
The main features of stuckatprototype/racer are: Autonomous Driving Stacks, Autonomous Vehicle Training, Model Inference, Neural Network Training, Supervised Learning Frameworks, 3D-Printable Robot Designs, Custom Robot Hardware Design, DIY Hardware Blueprints.
Projects with overlapping indexed features include: cpfl/autoware — Autoware is a modular autonomous driving stack and open-source platform for advanced driver assistance systems. It… deeplearning4j/deeplearning4j — Deeplearning4j is a JVM-based deep learning framework and tensor computing library. It provides a computational graph… stephencwelch/neural-networks-demystified — Neural Networks Demystified is an educational resource consisting of interactive Python notebooks designed to explain… autowarefoundation/autoware — Autoware is an open-source autonomous driving software platform built on the robotics middleware standard. It provides… apolloauto/apollo — Apollo is a comprehensive software stack designed for autonomous vehicle development, providing the necessary… opendrivelab/uniad — UniAD is a unified deep learning framework for autonomous driving that integrates perception, prediction, and planning…