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	Enabling In-Network Floating-Point Arithmetic for Efficient Computation Offloading 期刊论文 OAI收割 IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, 2022, 卷号: 33, 期号: 12, 页码: 4918-4934 作者: Cui, Penglai; Pan, Heng; Li, Zhenyu; Zhang, Penghao; Miao, Tianhao \| 收藏 \| 浏览/下载：23/0 \| 提交时间：2023/07/12 Open area test sites Arithmetic Memory management Task analysis Training Standards Servers In-network computation computation offloading floating-point operation
	NetSHa: In-Network Acceleration of LSH-Based Distributed Search 期刊论文 OAI收割 IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, 2022, 卷号: 33, 期号: 9, 页码: 2213-2229 作者: Zhang, Penghao; Pan, Heng; Li, Zhenyu; Cui, Penglai; Jia, Ru \| 收藏 \| 浏览/下载：48/0 \| 提交时间：2022/12/07 Servers Indexes Costs Task analysis Hash functions Concurrent computing Aggregates Local sensitive hashing distributed search in-network computation
	Moving target detection and classification using spiking neural networks (EI CONFERENCE) 会议论文 OAI收割 2nd Sino-Foreign-Interchange Workshop on Intelligent Science and Intelligent Data Engineering, IScIDE 2011, October 23, 2011 - October 25, 2011, Xi'an, China 作者: Sun H.; Wang Z.; Wang Z.; Wang P.; Sun H. 收藏 \| 浏览/下载：40/0 \| 提交时间：2013/03/25 We proposed a spiking neural network (SNN) to detect moving target in video streams and classify them into real categorization in this paper. The proposed SNN uses spike trains to encoding information such as the gray value of pixels or feature parameters of the target detects moving target by simulating the visual cortex for motion detection in biological system with axonal delays and classify them into different categorizations according to their distance to categorization's centers found by Hebb learning rule. The experimental results show that the proposed SNN is promising in intelligence computation and applicable in general visual surveillance system. 2012 Springer-Verlag.