1–20 von 23 Ergebnissen
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    Expert-driven Rule-based Refinement of Semantic Segmentation Maps for Autonomous Vehicles

    Manibardo, Eric L. / Lana, Ibai / Del Ser, Javier et al. | IEEE | 2023
    Semantic segmentation aims at assigning labels to every pixel of a given image. In the context of autonomous vehicles, semantic ...
    Verlag: IEEE

    RSG-Net: Towards Rich Sematic Relationship Prediction for Intelligent Vehicle in Complex Environments

    Tian, Yafu / Carballo, Alexander / Li, Ruifeng et al. | IEEE | 2021
    Behavioral and semantic relationships play a vital role on intelligent self-driving vehicles and ADAS systems. Different from other ...
    Verlag: IEEE

    How to monitor multiple autonomous vehicles remotely with few observers: An active management method

    Ding, Ming / Takeuchi, Eijiro / Ishiguro, Yoshio et al. | IEEE | 2021
    In this research, we proposed an active management method to tele-monitor and tele-operate more autonomous vehicles (AVs) with few ...
    Verlag: IEEE

    Continuous point cloud data compression using SLAM based prediction

    Tu, Chenxi / Takeuchi, Eijiro / Miyajima, Chiyomi et al. | IEEE | 2017
    Verlag: IEEE

    Synthesizing Realistic Snow Effects in Driving Images Using GANs and Real Data with Semantic Guidance*

    Yang, Hanting / Ding, Ming / Carballo, Alexander et al. | IEEE | 2023
    Intelligent vehicle perception algorithms often have difficulty accurately analyzing and interpreting images in adverse weather conditions ...
    Verlag: IEEE

    RSG-Search: Semantic Traffic Scene Retrieval Using Graph-Based Scene Representation

    Tian, Yafu / Carballo, Alexander / Li, Ruifeng et al. | IEEE | 2023
    , like "two vehicles waiting for a person crossing the road", is still an open problem. In this paper, we provide RSG-search, a scene-graph based ...
    Verlag: IEEE

    Real-to-Synthetic: Generating Simulator Friendly Traffic Scenes from Graph Representation

    Tian, Yafu / Carballo, Alexander / Li, Ruifeng et al. | IEEE | 2022
    Verlag: IEEE

    Real-Time Graph-Based Optimization for GNSS-Doppler Integrated RTK-GNSS/IMU/DR Positioning System in Urban Area

    Takanose, Aoki / Takeuchi, Eijiro / Carballo, Alexander et al. | IEEE | 2023
    Autonomous driving of vehicles and robots requires highly accurate position information, and RTK-GNSS is expected to be utilized for this ...
    Verlag: IEEE

    An enhanced driver’s risk perception modeling based on gate recurrent unit network

    Ping, Peng / Ding, Weiping / Liu, Yongkang et al. | IEEE | 2022
    Verlag: IEEE

    Uncertainty Aware Task Allocation for Human-Automation Cooperative Recognition in Autonomous Driving Systems

    Kuribayashi, Atsushi / Takeuchi, Eijiro / Carballo, Alexander et al. | IEEE | 2023
    Verlag: IEEE

    LiDAR Point Cloud Translation Between Snow and Clear Conditions Using Depth Images and GANs

    Zhang, Yuxiao / Ding, Ming / Yang, Hanting et al. | IEEE | 2023
    Verlag: IEEE

    OpenPlanner 2.0: The Portable Open Source Planner for Autonomous Driving Applications

    Darweesh, Hatem / Takeuchi, Eijiro / Takeda, Kazuya | IEEE | 2021
    suit a particular application. OpenPlanner 1.0 was introduced back in 2017 to fill this gap. It was developed and integrated with the open ...
    Verlag: IEEE

    Open-world driving scene segmentation via multi-stage and multi-modality fusion of vision-language embedding

    Niu, Yingjie / Ding, Ming / Zhang, Yuxiao et al. | IEEE | 2023
    Verlag: IEEE

    A Comparison of Methods for Sharing Recognition Information and Interventions to Assist Recognition in Autonomous Driving System

    Kuribayashi, Atsushi / Takeuchi, Eijiro / Carballo, Alexander et al. | IEEE | 2021
    Verlag: IEEE

    Driving Risk and Intervention: Subjective Risk Lane Change Dataset

    Bao, Naren / Carballo, Alexander / Takeda, Kazuya | IEEE | 2022
    Verlag: IEEE

    Point Grid Map-Based Mid-To-Mid Driving without Object Detection

    Seiya, Shunya / Carballo, Alexander / Takeuchi, Eijiro et al. | IEEE | 2020
    Teaching autonomous vehicles to imitate human driving in complex, urban traffic scenarios is a difficult task. “End-to-end ...
    Verlag: IEEE

    LIBRE: The Multiple 3D LiDAR Dataset

    Carballo, Alexander / Lambert, Jacob / Monrroy, Abraham et al. | IEEE | 2020
    ) facilitate the improvement of existing self-driving vehicles and robotics-related software, in terms of development and tuning of LiDAR-based ...
    Verlag: IEEE

    Automatic lane change extraction based on temporal patterns of symbolized driving behavioral data

    Mori, Masataka / Takenaka, Kazuhito / Bando, Takashi et al. | IEEE | 2015
    Verlag: IEEE

    Traffic trajectory history and drive path generation using GPS data cloud

    Yurtsever, Ekim / Takeda, Kazuya / Miyajima, Chiyomi | IEEE | 2015
    Verlag: IEEE