中国科学院机构知识库网格系统: 检索

BIRD plus : Design of a Lightweight Communication Compressor for Resource-Constrained Distribution Learning Platforms 期刊论文 OAI收割
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, 2024, 卷号: 35, 期号: 11, 页码: 2193-2207
作者: Wu, Donglei; Yang, Weihao; Zou, Xiangyu; Feng, Hao; Tao, Dingwen

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收藏 | 浏览/下载：4/0 | 提交时间：2024/12/06

Indexes Costs Computational modeling Distance learning Computer aided instruction Training Tensors Distributed learning communication compression random sampling neural network

Efficient Stereo Matching Using Swin Transformer and Multilevel Feature Consistency in Autonomous Mobile Systems 期刊论文 OAI收割
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2024, 页码: 9
作者: Su, Xiaojie; Liu, Shimin; Li, Rui

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收藏 | 浏览/下载：19/0 | 提交时间：2024/07/03

Costs Feature extraction Transformers Computational modeling Task analysis Image reconstruction Unsupervised learning Disparity estimation feature consistency stereo matching transformer

Optimizing Training Efficiency and Cost of Hierarchical Federated Learning in Heterogeneous Mobile-Edge Cloud Computing 期刊论文 OAI收割
IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS, 2023, 卷号: 42, 期号: 5, 页码: 1518-1531
作者: Cui, Yangguang; Cao, Kun; Zhou, Junlong; Wei, Tongquan

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收藏 | 浏览/下载：17/0 | 提交时间：2023/12/04

Training Servers Cloud computing Delays Costs Computational modeling Prototypes Device frequency determination federated learning (FL) high efficiency low cost mobile-edge cloud computing (MECC) user selection

A Low-Cost FPGA Implementation of Spiking Extreme Learning Machine With On-Chip Reward-Modulated STDP Learning 期刊论文 OAI收割
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS, 2022, 卷号: 69, 期号: 3, 页码: 1657-1661
作者: He, Zhen; Shi, Cong; Wang, Tengxiao; Wang, Ying; Tian, Min

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收藏 | 浏览/下载：44/0 | 提交时间：2022/12/07

Neurons Hardware System-on-chip Costs Training Field programmable gate arrays Computational modeling Neuromorphic computing spiking neural network extreme learning machine spike-timing-dependent plasticity reward-modulated on-chip learning

A Multi-Agent Reinforcement Learning Method With Route Recorders for Vehicle Routing in Supply Chain Management 期刊论文 OAI收割
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 页码: 11
作者: Ren, Lei; Fan, Xiaoyang; Cui, Jin; Shen, Zhen; Lv, Yisheng

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收藏 | 浏览/下载：31/0 | 提交时间：2022/06/06

Reinforcement learning Costs Task analysis Transportation Optimization Computational modeling Vehicle routing Vehicle routing supply chain management multi-agent reinforcement learning (MARL) route recorder

Development of zone flamelet modelfor scramjet combustor modeling 会议论文 OAI收割
Xiamen, China, March 6, 2017 - March 9, 2017
作者: Yao W(姚卫); Fan XJ(范学军)

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收藏 | 浏览/下载：36/0 | 提交时间：2018/11/08

Combustion Cost benefit analysis Costs Mixtures Ramjet engines Supersonic aircraft Computational costs Equivalence ratios Local flow conditions Scramjet combustors Statistics approaches Supersonic combustion Supersonic combustors Turbulent combustion

Numerical study of flow past a circular cylinder using SST kappa-omega, LES and ELES formulations 期刊论文 OAI收割
PROGRESS IN COMPUTATIONAL FLUID DYNAMICS, 2015, 卷号: 15, 期号: 4, 页码: 203-213
Hu, H. Z.; Hu, H. X.; Jiang, S. L.; Zheng, Y. G.

收藏 | 浏览/下载：19/0 | 提交时间：2016/04/21

shear-stress transport model large-eddy simulation embedded large eddy simulation ELES circular cylinder computational costs circular cylinder computational fluid dynamics CFD large eddy simulation LES turbulence model

Three-dimensional aeroacoustic numerical simulation of flow induced noise of mufflers 会议论文 OAI收割
26th International Conference on Parallel Computational Fluid Dynamics, ParCFD 2013, Changsha, China, May 20, 2013 - May 24, 2013
作者: Yang Y(杨焱); Sun HL

收藏 | 浏览/下载：47/0 | 提交时间：2017/05/27

CFD (computational fluid dynamics) Computation costs Computational aeroacoustics (CAA) Design and optimization Flow induced noise Non-linear acoustics Reynolds-Averaged Navier-Stokes Three-dimensional numerical simulations

A MLP-PNN neural network for CCD image super-resolution in wavelet packet domain (EI CONFERENCE) 会议论文 OAI收割
2008 International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2008, October 12, 2008 - October 14, 2008, Dalian, China
Zhao X.; Fu D.; Zhai L.

收藏 | 浏览/下载：68/0 | 提交时间：2013/03/25

Image super-resolution methods process an input image sequence of a scene to obtain a still image with increased resolution. Classical approaches to this problem involve complex iterative minimization procedures typically with high computational costs. In this paper is proposed a novel algorithm for super-resolution that enables a substantial decrease in computer load. First decompose and reconstruct the image by wavelet packet. Before constructing the image use neural network in place of other rebuilding method to reconstruct the coefficients in the wavelet packet domain. Second probabilistic neural network architecture is used to perform a scattered-point interpolation of the image sequence data in the wavelet packet domain. The network kernel function is optimally determined for this problem by a MLP-PNN (Multi Layer Perceptron - Probabilistic Neural Network) trained on synthetic data. Network parameters dependent on the sequence noise level. This super-sampled image is spatially Altered to correct finite pixel size effects to yield the final high-resolution estimate. This method can decrease the calculation cost and get perfect PSNR. Results are presented showing the quality of the proposed method. 2008 IEEE.

Real time tracking by LOPF algorithm with mixture model (EI CONFERENCE) 会议论文 OAI收割
MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, November 15, 2007 - November 17, 2007, Wuhan, China
Meng B.; Zhu M.; Han G.; Wu Z.

收藏 | 浏览/下载：27/0 | 提交时间：2013/03/25

A new particle filter-the Local Optimum Particle Filter (LOPF) algorithm is presented for tracking object accurately and steadily in visual sequences in real time which is a challenge task in computer vision field. In order to using the particles efficiently we first use Sobel algorithm to extract the profile of the object. Then we employ a new Local Optimum algorithm to auto-initialize some certain number of particles from these edge points as centre of the particles. The main advantage we do this in stead of selecting particles randomly in conventional particle filter is that we can pay more attentions on these more important optimum candidates and reduce the unnecessary calculation on those negligible ones in addition we can overcome the conventional degeneracy phenomenon in a way and decrease the computational costs. Otherwise the threshold is a key factor that affecting the results very much. So here we adapt an adaptive threshold choosing method to get the optimal Sobel result. The dissimilarities between the target model and the target candidates are expressed by a metric derived from the Bhattacharyya coefficient. Here we use both the counter cue to select the particles and the color cur to describe the targets as the mixture target model. The effectiveness of our scheme is demonstrated by real visual tracking experiments. Results from simulations and experiments with real video data show the improved performance of the proposed algorithm when compared with that of the standard particle filter. The superior performance is evident when the target encountering the occlusion in real video where the standard particle filter usually fails.