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arXiv 2024年

作者： Liu, Xiaohong Min, Xiongkuo Zhai, Guangtao Li, Chunyi Kou, Tengchuan Sun, Wei Wu, Haoning Gao, Yixuan Cao, Yuqin Zhang, Zicheng Wu, Xiele Timofte, Radu Gankhuyag, Ganzorig Yoon, Kihwan Xu, Yifang Fan, Haotian Kong, Fangyuan Zhao, Shiling Dong, Weifeng Yin, Haibing Zhu, Li Wang, Zhiling Huang, Bingchen Peng, Fei Fu, Huiyuan Ming, Anlong Wang, Chuanming Ma, Huadong He, Shuai Dou, Zifei Chen, Shu Yu, Zihao Guan, Fengbin Motamednia, Hossein Hosseini-Benvidi, S. Farhad Mahmoudi-Aznaveh, Ahmad Mansouri, Azadeh Saha, Avinab Mishra, Sandeep Gupta, Shashank Sureddi, Rajesh Saha, Oindrila Celona, Luigi Bianco, Simone Napoletano, Paolo Schettini, Raimondo Yang, Junfeng Fu, Jing Zhang, Wei Cao, Wenzhi Liu, Limei Peng, Han Yuan, Weijun Li, Zhan Cheng, Yihang Deng, Yifan Zhang, Huacong Xie, Haiyi Wang, Chengwei Chen, Baoying Zeng, Jishen Yang, Jianquan Wang, Weigang Fang, Xi Lv, Xiaoxin Yan, Jun Li, Haohui Qu, Bowen Li, Yao Luo, Shuqing Wang, Shunzhou Gao, Wei Lu, Zihao Conde, Marcos V. Timofte, Radu Lu, Yiting Li, Xin Wang, Xinrui Guan, Fengbin Chen, Zhibo Liao, Ruling Ye, Yan Wang, Qiulin Li, Bing Zhou, Zhaokun Geng, Miao Chen, Rui Tao, Xin Liang, Xiaoyu Sun, Shangkun Fang, Xi Wang, Weigang Yan, Jun Ma, Xingyuan Li, Jiaze Yang, Mengduo Xu, Haoran Zhou, Jie Zhu, Shiding Yu, Bohan Zhi, Tianwu Zhang, Yabin Li, Yaohui Li, Yang Xu, Jingwen Liu, Jianzhao Liao, Yiting Li, Junlin Chen, Baoying Zeng, Jishen Xie, Haiyi Wang, Chengwei Yang, Jianquan Chen, Pengfei Xu, Xinrui Shen, Jiabin Duan, Zhichao Liu, Jiahe Yan, Qi Qu, Youran Zeng, Xiaohui Wang, Lele Liao, Renjie Shanghai Jiao Tong University China Nanyang Technological University Singapore ETH Zürich Switzerland University of Würzburg Germany Korea Electronics Technology Institute Korea Republic of ByteDance China Hangzhou Dianzi University China Sankuai China Beijing University of Posts and Telecommunications China Beijing Xiaomi Mobile Software Co. Ltd. China University of Science and Technology of China China High Performance Computing Laboratory School of Computer Science Institute for Research in Fundamental Sciences Tehran Iran Department of Electrical and Computer Engineering Faculty of Engineering Kharazmi University Tehran Iran Cyber Research Institute Shahid Beheshti University Tehran Iran University of Texas Austin United States University of Massachusetts Amher United States Department of Informatics Systems and Communication Xiangjiang Laboratory Hunan University of Technology and Business China Jinan University China Sun Yat-sen University China Alibaba Group China Cisco Systems Inc. United States DP Technology Ltd. Shopee Pte. Ltd Tongji University China School of Electronic and Computer Engineering Shenzhen Graduate School Peking University China University of Würzburg Germany Kuaishou Technology China Peking University China Zhejiang University China Bytedance Inc China Xidian University China University of British Columbia Canada University of Toronto Canada

This paper reports on the NTIRE 2024 Quality Assessment of AI-Generated Content Challenge, which will be held in conjunction with the New Trends in Image Restoration and Enhancement Workshop (NTIRE) at CVPR 2024. This challenge is to address a major challenge in the field of image and video processing, namely, Image Quality Assessment (IQA) and Video Quality Assessment (VQA) for AI-Generated Content (AIGC). The challenge is divided into the image track and the video track. The image track uses the AIGIQA-20K, which contains 20,000 AI-Generated Images (AIGIs) generated by 15 popular generative models. The image track has a total of 318 registered participants. A total of 1,646 submissions are received in the development phase, and 221 submissions are received in the test phase. Finally, 16 participating teams submitted their models and fact sheets. The video track uses the T2VQA-DB, which contains 10,000 AI-Generated Videos (AIGVs) generated by 9 popular Text-to-Video (T2V) models. A total of 196 participants have registered in the video track. A total of 991 submissions are received in the development phase, and 185 submissions are received in the test phase. Finally, 12 participating teams submitted their models and fact sheets. Some methods have achieved better results than baseline methods, and the winning methods in both tracks have demonstrated superior prediction performance on AIGC. Copyright © 2024, The Authors. All rights reserved.

关键词： Image enhancement

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A Survey on Edge Detection based recent Marine Horizon Line Detection Methods and their Applications

A Survey on Edge Detection based recent Marine Horizon Line ...

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International Conference on computing, Mathematics and engineering Technologies (iCoMET)

作者： Manzoor Ahmed Hashmani Muhammad Umair Syed Sajjad Hussain Rizvi Abdul Rehman Gilal High-Performance Cloud Computing Center (HPC3) Center for Research in Data Science (CERDAS) Universiti Teknologi PETRONAS Seri Iskandar Malaysia High-Performance Cloud Computing Center (HPC3) Universiti Teknologi PETRONAS Seri Iskandar Malaysia Faculty of Engineering Sciences and Technology Hamdard University Karachi Pakistan Department of Computer Science Sukkur IBA University Sukkur Pakistan

ISBN: (数字)9781728149707

ISBN: (纸本)9781728149714

Sea and sky boundary identification (i.e. marine horizon line detection) from a marine image is a problem of great interest for reasons such as, unmanned surface or aerial vehicle navigation, surveillance by object detection and tracking, and determining the spatial orientation of the ship. Due to the complexity of the marine environment, the problem poses its own unique challenges. In recent years, different methods have been proposed by the researchers to solve the problem. Those methods can be grouped into two categories; (i) edge detection based horizon detection, and (ii) machine learning-based horizon detection. In this paper, we present a survey on edge detection based recent marine horizon line detection methods and their applications. We have selected studies from the previous three years and discussed each study's approach to marine horizon line detection issue, the datasets used for testing purposes and its results. The authors' observations for each study are presented with a recommendation for their suitability for a specific application in the marine environment. Findings of the survey and future research directions for the researchers are also identified and presented. We hope that this survey paper provides a comprehensive overview of edge detection based recent marine horizon line detection methods and help the researchers in exploring new solutions to this challenging problem.

关键词： Image edge detection Transforms Gray-scale Feature extraction Real-time systems Computational efficiency Image color analysis

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Inconsistencies among spectral robustness metrics 1

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14th EAI International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness, Qshine 2018

作者： Wang, Xiangrong Feng, Ling Kooij, Robert E. Marzo, Jose L. Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft Netherlands Computing Science Department Institute of High Performance Computing A*STAR Singapore Singapore iTrust Centre for Research in Cyber Security Singapore University of Technology and Design Singapore Singapore Institute of Informatics and Applications University of Girona Girona Spain

ISBN: (数字)9783030144135

ISBN: (纸本)9783030144128

Network robustness plays a critical role in the proper functioning of modern society. It is common practice to use spectral metrics, to quantify the robustness of networks. In this paper we compare eight different spectral metrics that quantify network robustness. Four of the metrics are derived from the adjacency matrix, the others follow from the Laplacian spectrum. We found that the metrics can give inconsistent indications, when comparing the robustness of different synthetic networks. Then, we calculate and compare the spectral metrics for a number of real-world networks, where inconsistencies still occur, but to a lesser extent. Finally, we indicate how the concept of the R∗-value, a weighted sum of robustness metrics, can be used to resolve the found inconsistencies. © ICST Institute for computer sciences, Social Informatics and Telecommunications engineering 2019.

关键词： Circuit theory

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high oscillator strength interlayer excitons in two-dimensional heterostructures for mid-infrared photodetection (vol 15, pg 675, 2020)

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NATURE NANOTECHNOLOGY 2021年第3期16卷 354-354页

作者： Lukman, Steven Ding, Lu Xu, Lei Tao, Ye Riis-Jensen, Anders C. Zhang, Gang Wu, Qing Yang Steve Yang, Ming Luo, Sheng Hsu, Chuanghan Yao, Liangzi Liang, Gengchiau Lin, Hsin Zhang, Yong-Wei Thygesen, Kristian S. Wang, Qi Jie Feng, Yuanping Teng, Jinghua Institute of Materials Research and Engineering Agency for Science Technology and Research (A*STAR) Singapore Singapore Department of Physics National University of Singapore Singapore Singapore School of Electrical and Electronic Engineering Nanyang Technological University Singapore Singapore CAMD and Center for Nanostructured Graphene (CNG) Department of Physics Technical University of Denmark Kongens Lyngby Denmark Institute of High Performance Computing Agency for Science Technology and Research (A*STAR) Singapore Singapore Department of Electrical and Computer Engineering Faculty of Engineering National University of Singapore Singapore Singapore Institute of Physics Academia Sinica Taipei Taiwan

A Correction to this paper has been published: https://***/10.1038/s41565-021-00865-9.

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Relativistic Quantum Calculations to Understand the Contribution of f-type Atomic Orbitals and Chemical Bonding of Actinides with Organic Ligands

arXiv

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arXiv 2021年

作者： Zapata-Escobar, Andy D. Pakhira, Srimanta Barroso-Flores, Joaquin Aucar, Gustavo A. Mendoza-Cortes, Jose L. Corrientes Argentina Indore453552 India Circuito Exterior SN Ciudad Universitaria Coyoacán Ciudad de MéxicoCP 04510 Mexico Physics Department Natural and Exact Science Faculty Northeastern University of Argentina Argentina Department of Physics Scientific Computing Material Sciences and Engineering High-Performance Material Institute Condensed Matter - High Magnetic Field National Lab Florida State University TallahasseeFL32310 United States Department of Chemical and Biomedical Engineering FAMU-FSU Joint College of Engineering TallahasseeFL32310 United States

The nuclear waste problem is one of the main interests of the rare earth and actinide elements chemistry. Studies of Actinide-containing compounds are at the frontier of the applications of current theoretical methods due to the need to consider relativistic effects and approximations to the Dirac equation in them. Here, we employ four-component relativistic quantum calculations and scalar approximations to understand the contribution of f-type atomic orbitals in the chemical bonding of actinides (Ac) to organic ligands. We studied the relativistic quantum structure of an isostructural family made of Plutonium (Pu), Americium (Am), Californium (Cf), and Berkelium (Bk) atoms with the redox-active model ligand;DOPO (2,4,6,8-tetra-tert-butyl-1-oxo-1H-phenoxazin-9-olate). Crystallographic structures were available to validate our calculations for all mentioned elements except for Cf. In short, state-of-the-art relativistic calculations were performed at different levels of theory to investigate the relativistic effects and electron correlations on geometrical structures and bonding energies of Ac-DOPO3 complexes (Ac=Pu, Am, Cf, Bk): 1) the scalar relativistic zeroth order regular approximation (ZORA) within the hybrid density functional theory (DFT) and 2) the four-component Dirac equation with the Dirac-Hartree-Fock (4c-DHF) and Lévy-Leblond (LL) Hamiltonians. We show that scalar DFT-ZORA could be used as an efficient theoretical approximation to first approximate the geometry and electronic properties of actinides which are difficult to synthesize or characterize;but knowing that the higher levels of theory, like the 4c-DHF, gives closer results to experiments than the scalar DFT-ZORA. We also performed spin-free calculations of geometric parameters for the Americium and Berkelium compounds. To the best of our knowledge, this is the first time that such kind of large actinide compounds (the largest contains 67 atoms and 421 electrons) are studied with highly accurate

关键词： Ligands

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NTIRE 2023 Quality Assessment of Video Enhancement Challenge

arXiv

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arXiv 2023年

作者： Liu, Xiaohong Min, Xiongkuo Sun, Wei Zhang, Yulun Zhang, Kai Timofte, Radu Zhai, Guangtao Gao, Yixuan Cao, Yuqin Kou, Tengchuan Dong, Yunlong Jia, Ziheng Li, Yilin Wu, Wei Hu, Shuming Deng, Sibin Xiao, Pengxiang Chen, Ying Li, Kai Zhao, Kai Yuan, Kun Sun, Ming Cong, Heng Wang, Hao Fu, Lingzhi Zhang, Yusheng Zhang, Rongyu Shi, Hang Xu, Qihang Xiao, Longan Ma, Zhiliang Agarla, Mirko Celona, Luigi Rota, Claudio Schettini, Raimondo Huang, Zhiwei Li, Yanan Wang, Xiaotao Lei, Lei Liu, Hongye Hong, Wei Chuang, Ironhead Lin, Allen Guan, Drake Chen, Iris Lou, Kae Huang, Willy Tasi, Yachun Kao, Yvonne Fan, Haotian Kong, Fangyuan Zhou, Shiqi Liu, Hao Lai, Yu Chen, Shanshan Wang, Wenqi Wu, Haoning Chen, Chaofeng Zhu, Chunzheng Guo, Zekun Zhao, Shiling Yin, Haibing Wang, Hongkui Meftah, Hanene Brachemi Fezza, Sid Ahmed Hamidouche, Wassim Déforges, Olivier Shi, Tengfei Mansouri, Azadeh Motamednia, Hossein Bakhtiari, Amir Hossein Aznaveh, Ahmad Mahmoudi Shanghai Jiao Tong University China ETH Zürich Switzerland University of Würzburg Germany Department of Tao Technology Alibaba Group China Kuaishou Technology China Interactive Entertainment Group of Netease Inc Guangzhou China Transsion China Vrobotit Lab Beijing University of Posts and Telecommunications China Hefei University of Technology China Department of Informatics Systems and Communication University of Milano - Bicocca Italy Xiaomi Inc. China China Ji Liang University China FreeTech China Advanced Research Center KKCompany Taiwan ByteDance China MGTV China Fuzhou University China Shopee Information Technology Co. Ltd. China S-Lab Nanyang Technological University Singapore Hunan University China Hangzhou Dianzi University China INSA Rennes CNRS IETR - UMR 6164 Rennes France National Higher School of Telecommunications and ICT Oran Algeria BUAA China Department of Electrical and Computer Engineering Faculty of Engineering Kharazmi University Tehran Iran High Performance Computing Laboratory School of Computer Science Institute for Research in Fundamental Sciences Tehran Iran Cyberspace Research Institute Shahid Beheshti University Tehran Iran

This paper reports on the NTIRE 2023 Quality Assessment of Video Enhancement Challenge, which will be held in conjunction with the New Trends in Image Restoration and Enhancement Workshop (NTIRE) at CVPR 2023. This challenge is to address a major challenge in the field of video processing, namely, video quality assessment (VQA) for enhanced videos. The challenge uses the VQA Dataset for Perceptual Video Enhancement (VDPVE), which has a total of 1211 enhanced videos, including 600 videos with color, brightness, and contrast enhancements, 310 videos with deblurring, and 301 deshaked videos. The challenge has a total of 167 registered participants. 61 participating teams submitted their prediction results during the development phase, with a total of 3168 submissions. A total of 176 submissions were submitted by 37 participating teams during the final testing phase. Finally, 19 participating teams submitted their models and fact sheets, and detailed the methods they used. Some methods have achieved better results than baseline methods, and the winning methods have demonstrated superior prediction performance. Copyright © 2023, The Authors. All rights reserved.

关键词： Image enhancement

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Characterisation of state-preparation uncertainty in quantum key distribution

arXiv

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arXiv 2022年

作者： Huang, Anqi Mizutani, Akihiro Lo, Hoi-Kwong Makarov, Vadim Tamaki, Kiyoshi Institute for Quantum Information State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha410073 China Graduate School of Engineering Science Osaka University Toyonaka Osaka560-8531 Japan Department of Electrical & Computer Engineering Department of Physics University of Toronto TorontoONM5S 3G4 Canada Department of Physics University of Hong Kong Pokfulam Hong Kong Quantum Bridge Technologies Inc. 100 College Street TorontoONM5G 1L5 Canada Russian Quantum Center Skolkovo Moscow121205 Russia Shanghai Branch National Laboratory for Physical Sciences at Microscale and CAS Center for Excellence in Quantum Information University of Science and Technology of China Shanghai201315 China NTI Center for Quantum Communications National University of Science and Technology MISiS Moscow119049 Russia Faculty of Engineering University of Toyama Gofuku 3190 Toyama930-8555 Japan

To achieve secure quantum key distribution, all imperfections in the source unit must be incorporated in a security proof and measured in the lab. Here we perform a proof-of-principle demonstration of the experimental techniques for characterising the source phase and intensity fluctuation in commercial quantum key distribution systems. When we apply the measured phase fluctuation intervals to the security proof that takes into account fluctuations in the state preparation, it predicts a key distribution distance of over 100 km of fiber. The measured intensity fluctuation intervals are however so large that the proof predicts zero key, indicating a source improvement may be needed. Our characterisation methods pave the way for a future certification standard. Copyright © 2022, The Authors. All rights reserved.

关键词： Quantum cryptography

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REFUGE2 CHALLENGE: A TREASURE TROVE FOR MULTI-DIMENSION ANALYSIS AND EVALUATION IN GLAUCOMA SCREENING

arXiv

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arXiv 2022年

作者： Fang, Huihui Li, Fei Wu, Junde Fu, Huazhu Sun, Xu Son, Jaemin Yu, Shuang Zhang, Menglu Yuan, Chenglang Bian, Cheng Lei, Baiying Zhao, Benjian Xu, Xinxing Li, Shaohua Fumero, Francisco Sigut, José Almubarak, Haidar Bazi, Yakoub Guo, Yuanhao Zhou, Yating Baid, Ujjwal Innani, Shubham Guo, Tianjiao Yang, Jie Orlando, José Ignacio Bogunović, Hrvoje Zhang, Xiulan Xu, Yanwu The REFUGE2 Challenge Australia State Key Laboratory of Ophthalmology Zhongshan Ophthalmic Center Sun Yat-Sen University Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science Guangzhou China Intelligent Healthcare Unit Baidu Inc. Beijing China The Institute of High Performance Computing Agency for Science Technology and Research Singapore Yatiris Group PLADEMA Institute CONICET UNICEN Tandil Argentina Christian Doppler Lab for Artificial Intelligence in Retina Department of Ophthalmology and Optometry Medical University of Vienna Vienna Austria VUNO Inc Seoul Korea Republic of Tencent HealthCare Tencent Shenzhen China Computer Vision Institute College of Computer Science and Software Engineering of Shenzhen University Shenzhen China School of Biomedical Engineering Health Science Center Shenzhen University China Xiaohe Healthcare ByteDance Guangdong Guangzhou510000 China School of Biomedical Engineering Shenzhen University China College of Computer Science & Software Engineering Shenzhen University China Department of Computer Science and Systems Engineering Universidad de La Laguna Spain Saudi Electronic University Saudi Arabia King Saud University Saudi Arabia Institute of Automation Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China SGGS Institute of Engineering and Technology India Institute of Medical Robotics Shanghai Jiao Tong University China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China

With the rapid development of artificial intelligence (AI) in medical image processing, deep learning in color fundus photography (CFP) analysis is also evolving. Although there are some open-source, labeled datasets of CFPs in the ophthalmology community, large-scale datasets for screening only have labels of disease categories, and datasets with annotations of fundus structures are usually small in size. In addition, labeling standards are not uniform across datasets, and there is no clear information on the acquisition device. Here we release a multi-annotation, multi-quality, and multi-device color fundus image dataset for glaucoma analysis on an original challenge-Retinal Fundus Glaucoma Challenge 2nd Edition (REFUGE2). The REFUGE2 dataset contains 2000 color fundus images with annotations of glaucoma classification, optic disc/cup segmentation, as well as fovea localization. Meanwhile, the REFUGE2 challenge sets three sub-tasks of automatic glaucoma diagnosis and fundus structure analysis and provides an online evaluation framework. Based on the characteristics of multi-device and multi-quality data, some methods with strong generalizations are provided in the challenge to make the predictions more robust. This shows that REFUGE2 brings attention to the characteristics of real-world multi-domain data, bridging the gap between scientific research and clinical application. © 2022, CC BY-NC-ND.

关键词： Color

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Preparing a commercial quantum key distribution system for certification against implementation loopholes

arXiv

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arXiv 2023年

作者： Makarov, Vadim Abrikosov, Alexey Chaiwongkhot, Poompong Fedorov, Aleksey K. Huang, Anqi Kiktenko, Evgeny Petrov, Mikhail Ponosova, Anastasiya Ruzhitskaya, Daria Tayduganov, Andrey Trefilov, Daniil Zaitsev, Konstantin Russian Quantum Center Skolkovo Moscow121205 Russia Vigo Quantum Communication Center University of Vigo VigoE-36310 Spain NTI Center for Quantum Communications National University of Science and Technology MISiS Moscow119049 Russia Department of Physics Faculty of Science Mahidol University Bangkok10400 Thailand Institute for Quantum Computing University of Waterloo WaterlooONN2L 3G1 Canada Department of Physics and Astronomy University of Waterloo WaterlooONN2L 3G1 Canada Bangkok10110 Thailand QRate Skolkovo Moscow143026 Russia Institute for Quantum Information State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha410073 China Steklov Mathematical Institute Russian Academy of Sciences Moscow119991 Russia atlanTTic Research Center University of Vigo VigoE-36310 Spain School of Telecommunication Engineering Department of Signal Theory and Communications University of Vigo VigoE-36310 Spain National Research University Higher School of Economics Moscow101000 Russia

A commercial quantum key distribution (QKD) system needs to be formally certified to enable its wide deployment. The certification should include the system’s robustness against known implementation loopholes and attacks that exploit them. Here we ready a fiber-optic QKD system for this procedure. The system has a prepare-and-measure scheme with decoy-state BB84 protocol, polarisation encoding, qubit source rate of 312.5 MHz, and is manufactured by QRate. We detail its hardware and post-processing. We analyse the hardware for known implementation loopholes, search for possible new loopholes, and discuss countermeasures. We then amend the system design to address the highest-risk loopholes identified. We also work out technical requirements on the certification lab and outline its possible structure. Copyright © 2023, The Authors. All rights reserved.

关键词： Quantum cryptography

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CDNET: A Content Delivery Network Emulator

CDNET: A Content Delivery Network Emulator

引用

International Symposium on Networks, computers and Communications (ISNCC)

作者： Hoang-Loc La Anh-Tu Ngoc Tran Masato Yoshimi Takuma Nakajima Nam Thoai High Performance Computing Laboratory Advanced Institute of Interdisciplinary Science and Technology Faculty of Computer Science and Engineering Ho Chi Minh City University of Technology (HCMUT) 268 Ly Thuong Kiet Street District 10 Ho Chi Minh City Vietnam Vietnam National University Ho Chi Minh City Linh Trung Ward Thu Duc District Ho Chi Minh City Vietnam Strategic Technology Center TIS Inc. Shinjuku-ku Tokyo Japan Service Strategy Sector TIS Inc. Shinjuku-ku Tokyo Japan

Analyzing Content Delivery Network (CDN) systems’ performance can help the CDNs’ owners increase their benefits, improve the systems’ service quality, and reduce investment costs. To analyze caching systems, besides mathematical models, there are simulation-based methods, which are based on virtual environments to mimic the system behaviors, typically, such as CDN simulators and testbeds. But these simulators and testbeds have their limitations. In particular, simulators cannot guarantee the functional realism of service applications. Meanwhile, testbeds are cumbersome and inflexible to adapt to new topologies or caching strategies. In this work, we develop a CDN emulator, which is adaptive, flexible, high-fidelity, and reliable. To evaluate the reproducibility of experimental results, we also run our tools multiple configuration parameter sets and compare the results with a discrete event simulation. Our experiments show that our emulator is stable and works properly. The tool’s resource consumption is also evaluated.

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