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Institution

Beijing University of Posts and Telecommunications

EducationBeijing, 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
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Journal ArticleDOI
TL;DR: In this paper, the authors designed and constructed a wideband balanced homodyne detector (BHD) based on radio frequency and integrated circuit technology, which shows bandwidth behavior up to 1.2 GHz and its quantum to classical noise ratio is around 18 dB.
Abstract: Balanced homodyne detector (BHD) that can measure the field quadratures of coherent states has been widely used in a range of quantum information technologies. Generally, the BHD tends to suffer from narrow bands and an expanding bandwidth behavior usually traps into a compromise with the gain, electronic noise, and quantum to classical noise ratio, etc. In this paper, we design and construct a wideband BHD based on radio frequency and integrated circuit technology. Our BHD shows bandwidth behavior up to 1.2 GHz and its quantum to classical noise ratio is around 18 dB. Simultaneously, the BHD has a linear performance with a gain of 4.86 k and its common mode rejection ratio has also been tested as 57.9 dB. With this BHD, the secret key rate of continuous-variable quantum key distribution system has a potential to achieve 66.55 Mb/s and 2.87 Mb/s, respectively, at the transmission distance of 10 and 45 km. Besides, with this BHD, the generation rate of quantum random number generator could reach up to 6.53 Gb/s.

86 citations

Posted Content
TL;DR: A novel CNN architecture named as ISGAN is proposed to conceal a secret gray image into a color cover image on the sender side and exactly extract the secret image out on the receiver side and can achieve start-of-art performances on LFW, PASCAL-VOC12 and ImageNet datasets.
Abstract: Nowadays, there are plenty of works introducing convolutional neural networks (CNNs) to the steganalysis and exceeding conventional steganalysis algorithms. These works have shown the improving potential of deep learning in information hiding domain. There are also several works based on deep learning to do image steganography, but these works still have problems in capacity, invisibility and security. In this paper, we propose a novel CNN architecture named as \isgan to conceal a secret gray image into a color cover image on the sender side and exactly extract the secret image out on the receiver side. There are three contributions in our work: (i) we improve the invisibility by hiding the secret image only in the Y channel of the cover image; (ii) We introduce the generative adversarial networks to strengthen the security by minimizing the divergence between the empirical probability distributions of stego images and natural images. (iii) In order to associate with the human visual system better, we construct a mixed loss function which is more appropriate for steganography to generate more realistic stego images and reveal out more better secret images. Experiment results show that ISGAN can achieve start-of-art performances on LFW, Pascal VOC2012 and ImageNet datasets.

86 citations

Journal ArticleDOI
TL;DR: This paper proposes a watermark strategy for quantum images that can be used to verify the identity of the true owner of a carrier image, and the proposed method’s capacity reaches the largest.
Abstract: Quantum watermarking is the technique which embeds the invisible quantum signal such as the owner’s identification into quantum multimedia data (such as audio, video and image) for copyright protection. In this paper, a watermark strategy for quantum images is proposed based on flexible representation for quantum images (FRQI). Compared with the former strategy, which can only be used to verify the identity of the true owner of a carrier image, the proposed method can be used to find out who is the real owner, and our strategy’s capacity reaches the largest. It is impossible for anyone except the copyrighter to clear off or extract the watermark images.

86 citations

Journal ArticleDOI
TL;DR: In this paper, a (2+1)-dimensional Davey-Stewartson system was proposed to describe the transformation of a wave-packet on water of finite depth.
Abstract: Under investigation in this paper is a (2+1)-dimensional Davey-Stewartson system, which describes the transformation of a wave-packet on water of finite depth. By virtue of the bell polynomials, bi...

85 citations

Journal ArticleDOI
TL;DR: This review summarizes the recent progresses of the applications of deep learning analysis on microscopic imaging, including scanning electron microscopy (SEM), transmission electron microscope (TEM), and scanning probe microscope (SPM), and presents sequentially the basic concepts ofdeep learning methods.

85 citations


Authors

Showing all 39925 results

NameH-indexPapersCitations
Jie Zhang1784857221720
Jian Li133286387131
Ming Li103166962672
Kang G. Shin9888538572
Lei Liu98204151163
Muhammad Shoaib97133347617
Stan Z. Li9753241793
Qi Tian96103041010
Xiaodong Xu94112250817
Qi-Kun Xue8458930908
Long Wang8483530926
Jing Zhou8453337101
Hao Yu8198127765
Mohsen Guizani79111031282
Muhammad Iqbal7796123821
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202394
2022533
20213,009
20203,720
20193,817
20183,296