Showing 4 open source projects for "self driving"

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  • 1
    CatBoost

    CatBoost

    High-performance library for gradient boosting on decision trees

    ...It has best in class prediction speed, supports both numerical and categorical features, has a fast and scalable GPU version, and readily comes with visualization tools. CatBoost was developed by Yandex and is used in various areas including search, self-driving cars, personal assistance, weather prediction and more.
    Downloads: 15 This Week
    Last Update:
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    Adaptive Intelligence

    Adaptive Intelligence

    Adaptive Intelligence also known as "Artificial General Intelligence"

    Adaptive Intelligence is the implementation of neural science, forensic psychology , behavioral science with machine-learning and artificial intelligence to provide advanced automated software platforms with the ability to adjust and thrive in dynamic environments by combining cognitive flexibility, emotional regulation, resilience, and practical problem-solving skills.
    Downloads: 6 This Week
    Last Update:
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  • 3
    BEVFormer

    BEVFormer

    Implementation of BEVFormer, a camera-only framework

    3D visual perception tasks, including 3D detection and map segmentation based on multi-camera images, are essential for autonomous driving systems. In this work, we present a new framework termed BEVFormer, which learns unified BEV representations with spatiotemporal transformers to support multiple autonomous driving perception tasks. In a nutshell, BEVFormer exploits both spatial and temporal information by interacting with spatial and temporal space through predefined grid-shaped BEV queries. ...
    Downloads: 0 This Week
    Last Update:
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  • 4
    neurojs

    neurojs

    A JavaScript deep learning and reinforcement learning library

    ...Several interactive demonstrations included with the project illustrate how neural networks can be used to train agents in simulated tasks, including a browser-based self-driving car example. These demos allow users to visualize how reinforcement learning agents improve their behavior over time as they receive rewards and update their neural networks.
    Downloads: 0 This Week
    Last Update:
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