Results 301 to 310 of about 19,754,425 (354)
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StarPerf: Characterizing Network Performance for Emerging Mega-Constellations
IEEE International Conference on Network Protocols, 2020"Newspace" mega-constellations, such as Starlink and OneWeb are gaining tremendous popularity, with the promising potential to provide high-capacity and low-latency communication globally.
Zeqi Lai, Hewu Li, Jihao Li
semanticscholar +1 more source
Capacity-Constrained Network Performance Model for Urban Rail Systems
Transportation Research Record, 2020This paper proposes a general network performance model (NPM) for monitoring the performance of urban rail systems using smart card data. NPM is a schedule-based network loading model with strict capacity constraints and boarding priorities.
Baichuan Mo +3 more
semanticscholar +1 more source
performing governance through networks
European Political Science, 2005Governance networks typically function in the absence of clearly defined constitutional rules. Network actors, therefore, have to develop a common understanding of the problem as well as build a basis for mutual trust. We suggest that discourse-analytical and dramaturgical concepts can be helpful instruments to analyse these dynamics of trust building ...
Hajer, M.A., Versteeg, W.B.
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2011
The book presents some key mathematical tools for the performance analysis of communication networks and computer systems.Communication networks and computer systems have become extremely complex. The statistical resource sharing induced by the random behavior of users and the underlying protocols and algorithms may affect Quality of Service.This book ...
Bonald, Thomas, Feuillet, Mathieu
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The book presents some key mathematical tools for the performance analysis of communication networks and computer systems.Communication networks and computer systems have become extremely complex. The statistical resource sharing induced by the random behavior of users and the underlying protocols and algorithms may affect Quality of Service.This book ...
Bonald, Thomas, Feuillet, Mathieu
openaire +2 more sources
High Performance Visual Tracking with Siamese Region Proposal Network
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018Visual object tracking has been a fundamental topic in recent years and many deep learning based trackers have achieved state-of-the-art performance on multiple benchmarks.
Bo Li +4 more
semanticscholar +1 more source
Performance Preserving Network Downscaling
38th Annual Simulation Symposium, 2005The Internet is a large, complex, heterogeneous system operating at very high speeds and consisting of a large number of users. Researchers use a suite of tools and techniques in order to understand the performance of networks: measurements, simulations, and deployments on small to medium-scale testbeds.
Govindan, Ramesh +2 more
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Network Pruning via Performance Maximization
Computer Vision and Pattern Recognition, 2021Channel pruning is a class of powerful methods for model compression. When pruning a neural network, it's ideal to obtain a sub-network with higher accuracy.
Shangqian Gao +3 more
semanticscholar +1 more source
Network Performance Analysis of Satellite–Terrestrial Vehicular Network
IEEE Internet of Things JournalThe low Earth orbit (LEO) satellite-assisted communications are envisioned as a prospective solution in next-generation networks to provide reliable, flexible, cost-effective, and globally seamless services.
Huaqing Wu +5 more
semanticscholar +1 more source
LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation
Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2020Graph Convolution Network (GCN) has become new state-of-the-art for collaborative filtering. Nevertheless, the reasons of its effectiveness for recommendation are not well understood.
Xiangnan He +5 more
semanticscholar +1 more source
Bi-Real Net: Binarizing Deep Network Towards Real-Network Performance
International Journal of Computer Vision, 2018In this paper, we study 1-bit convolutional neural networks (CNNs), of which both the weights and activations are binary. While being efficient, the lacking of a representational capability and the training difficulty impede 1-bit CNNs from performing as
Zechun Liu +5 more
semanticscholar +1 more source