Institution
University of Electronic Science and Technology of China
Education•Chengdu, China•
About: University of Electronic Science and Technology of China is a education organization based out in Chengdu, China. It is known for research contribution in the topics: Antenna (radio) & Dielectric. The organization has 50594 authors who have published 58502 publications receiving 711188 citations. The organization is also known as: UESTC.
Topics: Antenna (radio), Dielectric, Thin film, Radar, Artificial neural network
Papers published on a yearly basis
Papers
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TL;DR: A Hadamard product induced bias matrix model is proposed, which only requires the use of the data in the original matrix to identify and adjust the cardinally inconsistent element(s) in a PCM and significantly enhances matrix consistency and improves the reliability of PCM decision making.
240 citations
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TL;DR: In this paper, the formation of oxygen vacancy defects in BWO is responsible for the tuning band structure and modifying surface chemical state to improve carriers separation efficiency, enlarge visible light absorption range and facilitate reactant activation.
238 citations
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15 Jun 2019TL;DR: A deep learning architecture that produces accurate dense depth for the outdoor scene from a single color image and a sparse depth, which improves upon the state-of-the-art performance on KITTI depth completion benchmark.
Abstract: In this paper, we propose a deep learning architecture that produces accurate dense depth for the outdoor scene from a single color image and a sparse depth. Inspired by the indoor depth completion, our network estimates surface normals as the intermediate representation to produce dense depth, and can be trained end-to-end. With a modified encoder-decoder structure, our network effectively fuses the dense color image and the sparse LiDAR depth. To address outdoor specific challenges, our network predicts a confidence mask to handle mixed LiDAR signals near foreground boundaries due to occlusion, and combines estimates from the color image and surface normals with learned attention maps to improve the depth accuracy especially for distant areas. Extensive experiments demonstrate that our model improves upon the state-of-the-art performance on KITTI depth completion benchmark. Ablation study shows the positive impact of each model components to the final performance, and comprehensive analysis shows that our model generalizes well to the input with higher sparsity or from indoor scenes.
238 citations
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TL;DR: A highly sensitive electrocatalytic sensor designed and fabricated by the incorporation of NiO dope Pt nanostructure hybrid (NiO–Pt–H) showed an excellent catalytic activity and was used as a powerful tool for the determination of cysteamine in the presence of serotonin.
Abstract: A highly sensitive electrocatalytic sensor was designed and fabricated by the incorporation of NiO dope Pt nanostructure hybrid (NiO–Pt–H) as conductive mediator, bis (1,10 phenanthroline) (1,10-phenanthroline-5,6-dione) nickel(II) hexafluorophosphate (B,1,10,P,1,10, PDNiPF6), and electrocatalyst into carbon paste electrode (CPE) matrix for the determination of cysteamine. The NiO–Pt–H was synthesized by one-pot synthesis strategy and characterized by XRD, elemental mapping analysis (MAP), and FESEM methods. The characterization data, which confirmed good purity and spherical shape with a diameter of ⁓ 30.64 nm for the synthesized NiO–Pt–H. NiO–Pt–H/B,1,10, P,1,10, PDNiPF6/CPE, showed an excellent catalytic activity and was used as a powerful tool for the determination of cysteamine in the presence of serotonin. The NiO–Pt–H/B,1,10, P,1,10, PDNiPF6/CPE was able to solve the overlap problem of the two drug signals and was used for the determination of cysteamine and serotonin in concentration ranges of 0.003–200 µM and 0.5–260 µM with detection limits of 0.5 nM and 0.1 µM, using square wave voltammetric method, respectively. The NiO–Pt–H/B,1,10,P,1,10,PDNiPF6/CPE showed a high-performance ability for the determination of cysteamine and serotonin in the drug and pharmaceutical serum samples with the recovery data of 98.1–103.06%.
238 citations
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TL;DR: 6G is envisioned to include three major aspects, namely, mobile ultra-broadband, super Internet-of-Things (IoT), and artificial intelligence (AI), and key technologies to realize each aspect are reviewed.
Abstract: With a ten-year horizon from concept to reality, it is time now to start thinking about what will the sixth-generation (6G) mobile communications be on the eve of the fifth-generation (5G) deployment. To pave the way for the development of 6G and beyond, we provide 6G visions in this paper. We first introduce the state-of-the-art technologies in 5G and indicate the necessity to study 6G. By taking the current and emerging development of wireless communications into consideration, we envision 6G to include three major aspects, namely, mobile ultra-broadband, super Internet-of-Things (IoT), and artificial intelligence (AI). Then, we review key technologies to realize each aspect. In particular, teraherz (THz) communications can be used to support mobile ultra-broadband, symbiotic radio and satellite-assisted communications can be used to achieve super IoT, and machine learning techniques are promising candidates for AI. For each technology, we provide the basic principle, key challenges, and state-of-the-art approaches and solutions.
237 citations
Authors
Showing all 51090 results
Name | H-index | Papers | Citations |
---|---|---|---|
Gang Chen | 167 | 3372 | 149819 |
Frede Blaabjerg | 147 | 2161 | 112017 |
Kuo-Chen Chou | 143 | 487 | 57711 |
Yi Yang | 143 | 2456 | 92268 |
Guanrong Chen | 141 | 1652 | 92218 |
Shuit-Tong Lee | 138 | 1121 | 77112 |
Lei Zhang | 135 | 2240 | 99365 |
Rajkumar Buyya | 133 | 1066 | 95164 |
Lei Zhang | 130 | 2312 | 86950 |
Bin Wang | 126 | 2226 | 74364 |
Haiyan Wang | 119 | 1674 | 86091 |
Bo Wang | 119 | 2905 | 84863 |
Yi Zhang | 116 | 436 | 73227 |
Qiang Yang | 112 | 1117 | 71540 |
Chun-Sing Lee | 109 | 977 | 47957 |