Institution
Beijing University of Posts and Telecommunications
Education•Beijing, Beijing, China•
About: Beijing University of Posts and Telecommunications is a education organization based out in Beijing, Beijing, China. It is known for research contribution in the topics: MIMO & Quality of service. The organization has 39576 authors who have published 41525 publications receiving 403759 citations. The organization is also known as: BUPT.
Papers published on a yearly basis
Papers
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19 Feb 2018TL;DR: This work proposes a deep hashing framework for sketch retrieval that, for the first time, works on a multi-million scale human sketch dataset and shows that state-of-the-art hashing models specifically engineered for static images fail to perform well on temporal sketch data.
Abstract: We propose a deep hashing framework for sketch retrieval that, for the first time, works on a multi-million scale human sketch dataset. Leveraging on this large dataset, we explore a few sketch-specific traits that were otherwise under-studied in prior literature. Instead of following the conventional sketch recognition task, we introduce the novel problem of sketch hashing retrieval which is not only more challenging, but also offers a better testbed for large-scale sketch analysis, since: (i) more fine-grained sketch feature learning is required to accommodate the large variations in style and Abstraction, and (ii) a compact binary code needs to be learned at the same time to enable efficient retrieval. Key to our network design is the embedding of unique characteristics of human sketch, where (i) a two-branch CNN-RNN architecture is adapted to explore the temporal ordering of strokes, and (ii) a novel hashing loss is specifically designed to accommodate both the temporal and Abstract traits of sketches. By working with a 3.8M sketch dataset, we show that state-of-the-art hashing models specifically engineered for static images fail to perform well on temporal sketch data. Our network on the other hand not only offers the best retrieval performance on various code sizes, but also yields the best generalization performance under a zero-shot setting and when re-purposed for sketch recognition. Such superior performances effectively demonstrate the benefit of our sketch-specific design.
103 citations
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TL;DR: The proposed concept of generalizing DNA encryption as s-box substitution is expected to be beneficial for security evaluation and theoretical design of DNA-based image encryption schemes in the future.
103 citations
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TL;DR: This paper constructs an optimal signal generator, and proposes an embedded control scheme by embedding the generator in the feedback loop and proves that these algorithms with the embedded technique can guarantee the solvability of the problem for high-order multiagent systems under standard assumptions.
Abstract: In this paper, we study an optimal output consensus problem for a multiagent network with agents in the form of multi-input multioutput minimum-phase dynamics. Optimal output consensus can be taken as an extended version of the existing output consensus problem for higher-order agents with an optimization requirement, where the output variables of agents are driven to achieve a consensus on the optimal solution of a global cost function. To solve this problem, we first construct an optimal signal generator, and then propose an embedded control scheme by embedding the generator in the feedback loop. We give two kinds of algorithms based on different available information along with both state feedback and output feedback, and prove that these algorithms with the embedded technique can guarantee the solvability of the problem for high-order multiagent systems under standard assumptions.
103 citations
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15 Jun 2019TL;DR: A training strategy that treats the head data and the tail data in an unequal way, accompanying with noise-robust loss functions, to take full advantage of their respective characteristics and achieve the best result on MegaFace Challenge 2 given a large-scale noisy training data set is proposed.
Abstract: Large-scale face datasets usually exhibit a massive number of classes, a long-tailed distribution, and severe label noise, which undoubtedly aggravate the difficulty of training. In this paper, we propose a training strategy that treats the head data and the tail data in an unequal way, accompanying with noise-robust loss functions, to take full advantage of their respective characteristics. Specifically, the unequal-training framework provides two training data streams: the first stream applies the head data to learn discriminative face representation supervised by Noise Resistance loss; the second stream applies the tail data to learn auxiliary information by gradually mining the stable discriminative information from confusing tail classes. Consequently, both training streams offer complementary information to deep feature learning. Extensive experiments have demonstrated the effectiveness of the new unequal-training framework and loss functions. Better yet, our method could save a significant amount of GPU memory. With our method, we achieve the best result on MegaFace Challenge 2 (MF2) given a large-scale noisy training data set.
103 citations
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TL;DR: The physical-layer security in typical SM systems is explored and a secrecy rate analysis for multiple antenna destination and eavesdroppers receivers is presented, and the secrecy rate and transmission power tradeoff in active source jamming is demonstrated.
Abstract: In multiple-input–multiple-output (MIMO) wireless communications, spatial modulation (SM) has recently emerged as a new transmission method. This letter explores the physical-layer security in typical SM systems. We present a secrecy rate analysis for multiple antenna destination and eavesdroppers receivers. Targeting against passive eavesdroppers in unknown locations, we study the efficacy of active security measure through joint signal and jamming transmission without the typical requirement of eavesdropper channel information. We demonstrate the secrecy rate and transmission power tradeoff in active source jamming by providing numerical results on achieved secrecy rate and the bit error rate (BER) at different receivers.
103 citations
Authors
Showing all 39925 results
Name | H-index | Papers | Citations |
---|---|---|---|
Jie Zhang | 178 | 4857 | 221720 |
Jian Li | 133 | 2863 | 87131 |
Ming Li | 103 | 1669 | 62672 |
Kang G. Shin | 98 | 885 | 38572 |
Lei Liu | 98 | 2041 | 51163 |
Muhammad Shoaib | 97 | 1333 | 47617 |
Stan Z. Li | 97 | 532 | 41793 |
Qi Tian | 96 | 1030 | 41010 |
Xiaodong Xu | 94 | 1122 | 50817 |
Qi-Kun Xue | 84 | 589 | 30908 |
Long Wang | 84 | 835 | 30926 |
Jing Zhou | 84 | 533 | 37101 |
Hao Yu | 81 | 981 | 27765 |
Mohsen Guizani | 79 | 1110 | 31282 |
Muhammad Iqbal | 77 | 961 | 23821 |