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Creation of a Student Research Environment in Artificial Intelligence with Industrial Involvement

机译:创建人工智能与工业参与的学生研究环境

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In this paper we describe ongoing efforts in creating and using an environment for undergraduate research projects in Artificial Intelligence (AI). Our goal is to provide hands-on and real-world experience to students. Industry involvement in this environment provides partnership and supervision, based on deliverables. Students learn real-world skills related to AI in industry and this makes them employable in the job market which is experiencing growing demand for AI applications. The initial direction of the undergraduate research supported by this environment is related to ground based surveillance from stationary cameras where various aspects of human detection, human movement detection, and human movement classification are key components. The central theme of the research is how to use machine learning and computer vision to accomplish these goals and what hardware and software libraries should be selected. More specifically, we describe the research environment that consists of a laboratory with different stationary and remotely controlled cameras, including workstations with high end Graphical Processing Units (GPUs). Open source software libraries for machine learning and computer vision are used for advanced algorithm development in this environment. As a result our research environment has the following characteristics - it is geared towards attractive areas of machine learning and computer vision; and has preconfigured hardware and software components for experiments with data.
机译:在本文中,我们描述了在人工智能(AI)中为本科研究项目创造和使用环境的持续努力。我们的目标是为学生提供实践和现实世界的经验。行业参与本环境提供了基于可交付成果的伙伴关系和监督。学生学习与工业中的AI相关的真实技能,这使得它们在就业市场中可以在越来越多的AI应用需求。本环境支持的本科研究的初始方向与静止摄像机的地面监视有关,其中人类检测,人体运动检测和人体运动分类是关键部件。该研究的中央主题是如何使用机器学习和计算机愿望来完成这些目标以及应选择哪些硬件和软件库。更具体地,我们描述了由具有不同静止和远程控制摄像机的实验室组成的研究环境,包括具有高端图形处理单元(GPU)的工作站。用于机器学习和计算机视觉的开源软件库用于本环境中的高级算法开发。因此,我们的研究环境具有以下特点 - 它旨在朝向机器学习和计算机视觉的有吸引力的地区;并具有预先配置的硬件和软件组件,用于使用数据进行实验。

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