Výsledky vyhledávání - "Zhang Xingzhou"

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Hawk: An Efficient NALM System for Accurate Low-Power Appliance Recognition

Autor: Wang, Zijian, Zhang, Xingzhou, Wang, Yifan, Peng, Xiaohui, Xu, Zhiwei

Non-intrusive Appliance Load Monitoring (NALM) aims to recognize individual appliance usage from the main meter without indoor sensors. However, existing systems struggle to balance dataset construction efficiency and event/state recognition accuracy

Externí odkaz: http://arxiv.org/abs/2410.16293

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E$^3$-UAV: An Edge-based Energy-Efficient Object Detection System for Unmanned Aerial Vehicles

Autor: Suo, Jiashun, Zhang, Xingzhou, Shi, Weisong, Zhou, Wei

Publikováno v: IEEE Internet of Things Journal, Early Access 1-1 (2023)

Motivated by the advances in deep learning techniques, the application of Unmanned Aerial Vehicle (UAV)-based object detection has proliferated across a range of fields, including vehicle counting, fire detection, and city monitoring. While most exis

Externí odkaz: http://arxiv.org/abs/2308.04774

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HIT-UAV: A high-altitude infrared thermal dataset for Unmanned Aerial Vehicle-based object detection

Autor: Suo, Jiashun, Wang, Tianyi, Zhang, Xingzhou, Chen, Haiyang, Zhou, Wei, Shi, Weisong

Publikováno v: Sci Data 10, 227 (2023)

We present the HIT-UAV dataset, a high-altitude infrared thermal dataset for object detection applications on Unmanned Aerial Vehicles (UAVs). The dataset comprises 2,898 infrared thermal images extracted from 43,470 frames in hundreds of videos capt

Externí odkaz: http://arxiv.org/abs/2204.03245

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A Survey on Edge Computing Systems and Tools

Autor: Liu, Fang, Tang, Guoming, Li, Youhuizi, Cai, Zhiping, Zhang, Xingzhou, Zhou, Tongqing

Publikováno v: Proceedings of the IEEE, 2019

Driven by the visions of Internet of Things and 5G communications, the edge computing systems integrate computing, storage and network resources at the edge of the network to provide computing infrastructure, enabling developers to quickly develop an

Externí odkaz: http://arxiv.org/abs/1911.02794

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pCAMP: Performance Comparison of Machine Learning Packages on the Edges

Autor: Zhang, Xingzhou, Wang, Yifan, Shi, Weisong

Machine learning has changed the computing paradigm. Products today are built with machine intelligence as a central attribute, and consumers are beginning to expect near-human interaction with the appliances they use. However, much of the deep learn

Externí odkaz: http://arxiv.org/abs/1906.01878

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OpenEI: An Open Framework for Edge Intelligence

Autor: Zhang, Xingzhou, Wang, Yifan, Lu, Sidi, Liu, Liangkai, Xu, Lanyu, Shi, Weisong

In the last five years, edge computing has attracted tremendous attention from industry and academia due to its promise to reduce latency, save bandwidth, improve availability, and protect data privacy to keep data secure. At the same time, we have w

Externí odkaz: http://arxiv.org/abs/1906.01864

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