面向目标检测的数据挖掘硬件加速

Narges Attarmoghaddam, K. F. Li
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引用次数: 2

摘要

在过去的十年中,由于其在智能机器人,智能家居,监控和监视等领域的许多应用,物体检测一直是计算机视觉领域的一个活跃的研究领域。这些应用中对实时检测的需求以及基于软件的实现在实现实时能力方面的频繁失败促使研究人员利用硬件加速。由于具有并行性、低功耗和可重构性的潜力,现场可编程门阵列(FPGA)器件非常适合于目标检测系统的实现。在这项调查中,我们研究了基于fpga的使用数据挖掘算法的目标检测系统的实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data Mining Hardware Acceleration for Object Detection
Over the past decade, object detection has been an active research area in the field of computer vision due to its many applications such as intelligent robots, smart homes, monitoring and surveillance. The need for real-time detection in most of these applications and the frequent failure of software-based implementations in achieving real-time capability, has motivated researchers to utilize hardware acceleration. Due to the potential for parallelism, low power and reconfigurability, Field Programmable Gate Array (FPGA) devices are well-suited for object detection system implementation. In this survey, we investigate FPGA-based implementation of object detection systems using data mining algorithms.
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