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High performance DT-CNN camera device design on ACTEL IGLOO low power FPGA

机译:基于ACTEL IGLOO低功耗FPGA的高性能DT-CNN摄像头设备设计

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In this paper we present a complete study on the balance between high performance image processing and low power consumption without using expensive components. Our proposal consists in implementing a Discrete Time Cellular Neural Network (DT-CNN) on a low power Actel IGLOO nano Field Programmable Gate Array (FPGA). This is a definitive step further from previous work to obtain an intelligent camera device for robots. Applications in Robot Guidance have rapidly increased in the last years as robots break in different fields of everyday live, which most of this robotic devices need sensors for navigation. Our proposed low cost solution avoids highly complex architectures, expensive smart sensors and low performance navigation systems.
机译:在本文中,我们对高性能图像处理和低功耗之间的平衡进行了完整的研究,而无需使用昂贵的组件。我们的建议包括在低功耗Actel IGLOO纳米现场可编程门阵列(FPGA)上实现离散时间细胞神经网络(DT-CNN)。这是获得机器人智能相机设备的最后一步。近年来,随着机器人在日常生活的不同领域中突围,机器人制导中的应用迅速增长,其中大多数此类机器人设备都需要用于导航的传感器。我们提出的低成本解决方案避免了高度复杂的架构,昂贵的智能传感器和低性能的导航系统。

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