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A deep learning-based binocular perception system

机译:基于深度学习的双目感知系统

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摘要

An obstacle perception system for intelligent vehicle is proposed. The proposed system combines the stereo version technique and the deep learning network model, and is applied to obstacle perception tasks in complex environment. In this paper, we provide a complete system design project, which includes the hardware parameters, software framework, algorithm principle, and optimization method. In addition, special experiments are designed to demonstrate that the performance of the proposed system meets the requirements of actual application. The experiment results show that the proposed system is valid to both standard obstacles and non-standard obstacles, and suitable for different weather and lighting conditions in complex environment. It announces that the proposed system is flexible and robust to the intelligent vehicle.
机译:提出了一种智能车辆的障碍物感知系统。所提出的系统结合了立体声版技术和深度学习网络模型,并应用于复杂环境中的障碍感知任务。在本文中,我们提供了一个完整的系统设计项目,包括硬件参数,软件框架,算法原理和优化方法。此外,特殊实验旨在证明所提出的系统的性能符合实际应用的要求。实验结果表明,该系统对标准障碍和非标准障碍有效,适用于复杂环境中的不同天气和照明条件。它宣布,建议的系统对智能车辆灵活且鲁棒。

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