Institution
Huawei
Company•Shenzhen, China•
About: Huawei is a company organization based out in Shenzhen, China. It is known for research contribution in the topics: Terminal (electronics) & Node (networking). The organization has 41417 authors who have published 44698 publications receiving 343496 citations. The organization is also known as: Huawei Technologies & Huawei Technologies Co., Ltd..
Papers published on a yearly basis
Papers
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ETH Zurich1, Hong Kong Polytechnic University2, Shanghai Jiao Tong University3, Microsoft4, Korea University5, Ajou University6, École Polytechnique Fédérale de Lausanne7, University of Udine8, Dalian Maritime University9, Tencent10, Peking University11, North China University of Technology12, Huawei13, Fuzhou University14, Samsung15, Ulsan National Institute of Science and Technology16, Sardar Vallabhbhai National Institute of Technology, Surat17, Norwegian University of Science and Technology18
TL;DR: The NTIRE 2020 challenge as discussed by the authors addressed the real world setting, where paired true high and low-resolution images are unavailable, for training, only one set of source input images is provided along with a set of unpaired high-quality target images.
Abstract: This paper reviews the NTIRE 2020 challenge on real world super-resolution. It focuses on the participating methods and final results. The challenge addresses the real world setting, where paired true high and low-resolution images are unavailable. For training, only one set of source input images is therefore provided along with a set of unpaired high-quality target images. In Track 1: Image Processing artifacts, the aim is to super-resolve images with synthetically generated image processing artifacts. This allows for quantitative benchmarking of the approaches w.r.t. a ground-truth image. In Track 2: Smartphone Images, real low-quality smart phone images have to be super-resolved. In both tracks, the ultimate goal is to achieve the best perceptual quality, evaluated using a human study. This is the second challenge on the subject, following AIM 2019, targeting to advance the state-of-the-art in super-resolution. To measure the performance we use the benchmark protocol from AIM 2019. In total 22 teams competed in the final testing phase, demonstrating new and innovative solutions to the problem.
91Â citations
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TL;DR: This service-side solution uses graph data mining to distinguish spammers from nonspammers and detect spam without checking a message's contents.
Abstract: Short Message Service text messages are indispensable, but they face a serious problem from spamming. This service-side solution uses graph data mining to distinguish spammers from nonspammers and detect spam without checking a message's contents.
90Â citations
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15 Apr 2018TL;DR: This paper proposes a novel optimization framework which allows fine-grained resource allocation for slices both in terms of network bandwidth and cloud processing and demonstrates the method's fast convergence in a wide range of quasi-stationary and dynamic settings.
Abstract: Telecommunication networks are converging to a massively distributed cloud infrastructure interconnected with software defined networks. In the envisioned architecture, services will be deployed flexibly and quickly as network slices. Our paper addresses a major bottleneck in this context, namely the challenge of computing the best resource provisioning for network slices in a robust and efficient manner. With tractability in mind, we propose a novel optimization framework which allows fine-grained resource allocation for slices both in terms of network bandwidth and cloud processing. The slices can be further provisioned and auto-scaled optimally based on a large class of utility functions in real-time. Furthermore, by tuning a slice-specific parameter, system designers can trade off traffic-fairness with computing-fairness to provide a mixed fairness strategy. We also propose an iterative algorithm based on the alternating direction method of multipliers (ADMM) that provably converges to the optimal resource allocation and we demonstrate the method's fast convergence in a wide range of quasi-stationary and dynamic settings.
90Â citations
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27 Feb 2006TL;DR: In this article, a user interface is generated that displays a user selectable indicia representing a similar member function for allowing a user to search a media service for at least one other user which has a degree of similarity with respect to the searching user.
Abstract: A method and computer readable medium for exploring similar users and items of a media service. In one aspect, a user can explore for similar users iteratively. In one aspect, a user interface is generated that displays a user selectable indicia representing a similar member function for allowing a user to search a media service for at least one other user which has a degree of similarity with respect to the searching user. In another aspect, a method facilitates the search of such a similar user within a media service.
90Â citations
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TL;DR: A converged 5G network infrastructure and an overarching architecture to jointly support operational network and end-user services, proposed by the EU 5G PPP project 5G-XHaul are presented.
Abstract: This article presents a converged 5G network infrastructure and an overarching architecture to jointly support operational network and end-user services, proposed by the EU 5G PPP project 5G-XHaul. The 5G-XHaul infrastructure adopts a common fronthaul/backhaul network solution, deploying a wealth of wireless technologies and a hybrid active/passive optical transport, supporting flexible fronthaul split options. This infrastructure is evaluated through a novel modeling. Numerical results indicate significant energy savings at the expense of increased end-user service delay.
90Â citations
Authors
Showing all 41483 results
Name | H-index | Papers | Citations |
---|---|---|---|
Yu Huang | 136 | 1492 | 89209 |
Xiaoou Tang | 132 | 553 | 94555 |
Xiaogang Wang | 128 | 452 | 73740 |
Shaobin Wang | 126 | 872 | 52463 |
Qiang Yang | 112 | 1117 | 71540 |
Wei Lu | 111 | 1973 | 61911 |
Xuemin Shen | 106 | 1221 | 44959 |
Li Chen | 105 | 1732 | 55996 |
Lajos Hanzo | 101 | 2040 | 54380 |
Luca Benini | 101 | 1453 | 47862 |
Lei Liu | 98 | 2041 | 51163 |
Tao Wang | 97 | 2720 | 55280 |
Mohamed-Slim Alouini | 96 | 1788 | 62290 |
Qi Tian | 96 | 1030 | 41010 |
Merouane Debbah | 96 | 652 | 41140 |