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Image Processing and Vehicles – Using FPGA to Reduce Latency of Time Critical Tasks

机译:图像处理和车辆 - 使用FPGA减少时间关键任务的延迟

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When automating complex vision-controlled objects such as self-driving cars, large amounts of data need to be processed accurately, quickly and reliably at video frame rates. In this paper we propose the use of an Intel Cyclone V FPGA to process image data in a parallel form, building a safe real-time system. We discuss the hardware used to build the physical prototype and the control algorithms to build the control architecture that controls the prototype.
机译:当自动化自动驾驶汽车等复杂视觉控制物体时,需要在视频帧速率下准确,快速可靠地处理大量数据。在本文中,我们提出了使用Intel Cyclone V FPGA以并行形式处理图像数据,构建安全的实时系统。我们讨论用于构建物理原型和控制算法的硬件,以构建控制原型的控制架构。

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