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Subspace Support Vector Data Description

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arXiv 2018年

作者： Sohrab, Fahad Raitoharju, Jenni Gabbouj, Moncef Iosifidis, Alexandros Laboratory of Signal Processing Tampere University of Technology Finland Department of Engineering Electrical and Computer Engineering Aarhus University Denmark

This paper proposes a novel method for solving one-class classification problems. The proposed approach, namely Subspace Support Vector Data Description, maps the data to a subspace that is optimized for one-class classification. In that feature space, the optimal hypersphere enclosing the target class is then determined. The method iteratively optimizes the data mapping along with data description in order to define a compact class representation in a low-dimensional feature space. We provide both linear and non-linear mappings for the proposed method. Experiments on 14 publicly available datasets indicate that the proposed Subspace Support Vector Data Description provides better performance compared to baselines and other recently proposed one-class classification methods. Copyright © 2018, The Authors. All rights reserved.

关键词： Data description

Secure Edge Caching Placement and Delivery for Ultra-Reliable and Low-Latency Vehicular Networks

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Secure Edge Caching Placement and Delivery for Ultra-Reliabl...

IEEE Globecom Workshops

作者： Haojun Yang Kuan Zhang Kan Zheng Yi Qian Intelligent Computing and Communications (IC) Lab Wireless Signal Processing and Networks (WSPN) Lab Key Laboratory of Universal Wireless Communications Ministry of Education Beijing University of Posts and Telecommunications Beijing China Department of Electrical and Computer Engineering University of Nebraska-Lincoln Omaha NE USA

ISBN: (数字)9781728109602

ISBN: (纸本)9781728109619

To meet the urgent requirements of ultra-reliable and low-latency communications (URLLCs) in vehicular networks, vehicular edge caching (VEC) becomes a promising solution to reduce backhaul costs and mitigate network congestion. However, the data requested by vehicular users may be maliciously tampered by attackers during the caching delivery phase. In this paper, we investigate the problem of secure caching placement and delivery for a VEC URLLC system. Specifically, we first analyze the lower bound of spectral efficiency for URLLCs and security metric, i.e., vulnerability. Then, an optimization problem of minimizing the maximum vulnerability among all vehicular users is formulated based on the analysis. Subsequently, we propose a secure caching placement and delivery algorithm to obtain the solutions of our formulated problem by reasonable complexity. Simulation results show that the proposed algorithm can significantly improve the performance of security for the VEC URLLC system.

关键词： Security Optimization Roads Reliability Fading channels signal to noise ratio Antennas

OCTAVA: An open-source toolbox for quantitative analysis of optical coherence tomography angiography images

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arXiv 2021年

作者： Untracht, Gavrielle R. Matos, Rolando Dikaios, Nikolaos Bapir, Mariam Durrani, Abdullah K. Butsabong, Teemapron Campagnolo, Paola Sampson, David D. Heiss, Christian Sampson, Danuta M. Optical+Biomedical Engineering Laboratory School of Electrical Electronic and Computer Engineering The University of Western Australia 35 Stirling Highway PerthWA6009 Australia Surrey Biophotonics Advanced Technology Institute School of Physics School of Biosciences and Medicine University of Surrey Surrey GuildfordGU2 7XH United Kingdom Department of Biochemical Sciences Department of Clinical and Experimental Medicine School of Biosciences and Medicine University of Surrey Surrey GuildfordGU2 7XH United Kingdom Mathematics Research Center Academy of Athens Athens106 79 Greece Surrey and Sussex Healthcare NHS Trust East Surrey Hospital Surrey RedhillRH1 5RH United Kingdom Surrey Biophotonics Centre for Vision Speech and Signal Processing School of Biosciences and Medicine The University of Surrey GuildfordGU2 7XH United Kingdom

Optical coherence tomography angiography (OCTA) performs non-invasive visualization and characterization of microvasculature in research and clinical applications mainly in ophthalmology and dermatology. A wide variety of instruments, imaging protocols, processing methods and metrics have been used to describe the microvasculature, such that comparing different study outcomes is currently not feasible. With the goal of contributing to standardization of OCTA data analysis, we report a user-friendly, open-source toolbox, OCTAVA (OCTA Vascular Analyzer), to automate the pre-processing, segmentation, and quantitative analysis of en face OCTA maximum intensity projection images in a standardized workflow. We present each analysis step, including optimization of filtering and choice of segmentation algorithm, and definition of metrics. We perform quantitative analysis of OCTA images from different commercial and non-commercial instruments and samples and show OCTAVA can accurately and reproducibly determine metrics for characterization of microvasculature. Wide adoption could enable studies and aggregation of data on a scale sufficient to develop reliable microvascular biomarkers for early detection, and to guide treatment, of microvascular disease. © 2021, CC BY-NC-SA.

关键词： Optical tomography

NTIRE 2020 Challenge on image and Video Deblurring

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arXiv 2020年

作者： Seungjun, Nah Sanghyun, Son Radu, Timofte Kyoung Mu, Lee Tseng, Yu Xu, Yu-Syuan Chiang, Cheng-Ming Tsai, Yi-Min Brehm, Stephan Scherer, Sebastian Xu, Dejia Chu, Yihao Sun, Qingyan Jiang, Jiaqin Duan, Lunhao Yao, Jian Purohit, Kuldeep Suin, Maitreya Rajagopalan, A.N. Ito, Yuichi Hrishikesh, P.S. Puthussery, Densen Akhil, K.A. Jiji, C.V. Kim, Guisik Deepa, P.L. Xiong, Zhiwei Huang, Jie Liu, Dong Kim, Sangmin Nam, Hyungjoon Kim, Jisu Jeong, Jechang Huang, Shihua Fan, Yuchen Yu, Jiahui Yu, Haichao Huang, Thomas S. Zhou, Ya Li, Xin Liu, Sen Chen, Zhibo Dutta, Saikat Das, Sourya Dipta Garg, Shivam Sprague, Daniel Patel, Bhrij Huck, Thomas Department of ECE ASRI SNU Korea Republic of Computer Vision Lab ETH Zurich Switzerland MediaTek Inc University of Augsburg Chair for Multimedia Computing and Computer Vision Lab Germany Peking University China Beijing University of Posts and Telecommunications China Beijing Jiaotong University China Wuhan University China Indian Institute of Technology Madras India Vermilion College of Engineering Trivandrum India CVML Chung-Ang University Korea Republic of APJ Abdul Kalam Technological University India University of Science and Technology of China China Image Communication Signal Processing Laboratory Hanyang University Korea Republic of Southern University of Science and Technology China University of Illinois at Urbana-Champaign United States CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System University of Science and Technology of China China IIT Madra Jadavpur University India University of Texas Austin United States Duke University Computer Science Department United States

Motion blur is one of the most common degradation artifacts in dynamic scene photography. This paper reviews the NTIRE 2020 Challenge on image and Video Deblurring. In this challenge, we present the evaluation results from 3 competition tracks as well as the proposed solutions. Track 1 aims to develop single-image deblurring methods focusing on restoration quality. On Track 2, the image deblurring methods are executed on a mobile platform to find the balance of the running speed and the restoration accuracy. Track 3 targets developing video deblurring methods that exploit the temporal relation between input frames. In each competition, there were 163, 135, and 102 registered participants and in the final testing phase, 9, 4, and 7 teams competed. The winning methods demonstrate the state-of-the-art performance on image and video deblurring tasks. Copyright © 2020, The Authors. All rights reserved.

关键词： image enhancement

Granular Computing: An Augmented Scheme of Degranulation Through a Modified Partition Matrix

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arXiv 2020年

作者： Xu, Kaijie Pedrycz, Witold Li, Zhiwu Xing, Mengdao School of Electro-Mechanical Engineering Xidian University Xi’an710071 China Department of remote sensing science and technology School of Electronic Engineering Xidian University Xi’an710071 China Department of Electrical and Computer Engineering University of Alberta EdmontonABT6R 2V4 Canada Systems Research Institute Polish Academy of Sciences Warsaw Poland Faculty of Engineering King Abdulaziz University Jeddah21589 Saudi Arabia Institute of Systems Engineering Macau University of Science and Technology Macau999078 China National Laboratory of Radar Signal Processing Xidian University Xi’an710071 China Collaborative Innovation Center of Information Sensing and Understanding Xidian University Xi’an710071 China National Key Laboratory of Microwave Imaging Technology Institute of Electronics Chinese Academy of Sciences Beijing100190 China

As an important technology in artificial intelligence Granular Computing (GrC) has emerged as a new multi-disciplinary paradigm and received much attention in recent years. Information granules forming an abstract and efficient characterization of large volumes of numeric data have been considered as the fundamental constructs of GrC. By generating centroids (prototypes) and partition matrix, fuzzy clustering is a commonly encountered way of information granulation. As a reverse process of granulation, degranulation involves data reconstruction completed on a basis of the granular representatives (decoding information granules into numeric data). Previous studies have shown that there is a relationship between the reconstruction error and the performance of the granulation process. Typically, the lower the degranulation error is, the better performance of granulation process becomes. However, the existing methods of degranulation usually cannot restore the original numeric data, which is one of the important reasons behind the occurrence of the reconstruction error. To enhance the quality of reconstruction (degranulation), in this study, we develop an augmented scheme through modifying the partition matrix. By proposing the augmented scheme, we dwell on a novel collection of granulation-degranulation mechanisms. In the constructed approach, the prototypes can be expressed as the product of the dataset matrix and the partition matrix. Then, in the degranulation process, the reconstructed numeric data can be decomposed into the product of the partition matrix and the matrix of prototypes. Both the granulation and degranulation are regarded as generalized rotation between the data subspace and the prototype subspace with the partition matrix and the fuzzification factor. By modifying the partition matrix, the new partition matrix is constructed through a series of matrix operations. We offer a thorough analysis of the developed scheme. Copyright © 2020, The Authors. Al

关键词： Granulation

Tunable superconducting josephson dielectric metamaterial

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arXiv 2019年

作者： Trepanier, M. Zhang, Daimeng Filippenko, L.V. Koshelets, V.P. Anlage, Steven M. Center for Nanophysics and Advanced Materials Department of Physics University of Maryland College ParkMD20742-4111 United States Department of Electrical and Computer Engineering University of Maryland College ParkMD20742-3285 United States Laboratory of Superconducting Devices for Signal Detection and Processing Kotelnikov Institute of Radio Engineering and Electronics Moscow125009 Russia

We demonstrate a low-dissipation dielectric metamaterial with tunable properties based on the Josephson effect. Superconducting wires loaded with regularly spaced Josephson junctions (critical current Ic ≈ 0.25 µA) spanning a K-band waveguide and aligned with the microwave electric fields create a superconducting dielectric metamaterial. Applied dc current tunes the cutoff frequency and effective permittivity of this unique electric metamaterial. The results are in agreement with an analytical model for microwave transmission through the artificial dielectric medium. Copyright © 2019, The Authors. All rights reserved.

关键词： Metamaterials

Weighted linear discriminant analysis based on class saliency information

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arXiv 2018年

作者： Xu, Lei Iosifidis, Alexandros Gabbouj, Moncef Laboratory of Signal Processing Tampere University of Technology Tampere Finland Department of Engineering Electrical and Computer Engineering Aarhus University Aarhus Denmark

In this paper, we propose a new variant of Linear Discriminant Analysis to overcome underlying drawbacks of traditional LDA and other LDA variants targeting problems involving imbalanced classes. Traditional LDA sets assumptions related to Gaussian class distribution and neglects influence of outlier classes, that might hurt in performance. We exploit intuitions coming from a probabilistic interpretation of visual saliency estimation in order to define saliency of a class in multi-class setting. Such information is then used to redefine the between-class and within-class scatters in a more robust manner. Compared to traditional LDA and other weight-based LDA variants, the proposed method has shown certain improvements on facial image classification problems in publicly available datasets. Copyright © 2018, The Authors. All rights reserved.

关键词： Visualization

WEIGHTED LINEAR DISCRIMINANT ANALYSIS BASED ON CLASS SALIENCY INFORMATION

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WEIGHTED LINEAR DISCRIMINANT ANALYSIS BASED ON CLASS SALIENC...

IEEE International Conference on image processing

作者： Lei Xu Alexandros Iosifidis Moncef Gabbouj Laboratory of Signal Processing Tampere University of Technology Tampere Finland Department of Engineering Electrical & Computer Engineering Aarhus University Aarhus Denmark

关键词： Estimation Probabilistic logic Visualization Optimization Linear discriminant analysis Task analysis Robustness

Radiomics analysis of baseline F-FDG PET/CT images for improved prognosis in nasopharyngeal carcinoma 15

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Radiomics analysis of baseline F-FDG PET/CT images for impro...

15th IEEE International Symposium on Biomedical Imaging, ISBI 2018

作者： Lv, Wenbing Yuan, Qingyu Wang, Quanshi Ma, Jianhua Feng, Qianjin Chen, Wufan Rahmim, Arman Lu, Lijun School of Biomedical Engineering and Guangdong Provincial Key Laboratory of Medical Image Processing Southern Medical University China Nanfang PET Center Nanfang Hospital Southern Medical University China Department of Radiology Johns Hopkins University United States Department of Electrical and Computer Engineering Johns Hopkins University United States

ISBN: (纸本)9781538636367

The purpose of this study is to investigate the prognostic performance of radiomics features on nasopharyngeal carcinoma (NPC) patients imaged with baseline 18F-FDG PET/CT. 128 NPC patients were retrospectively enrolled with 3348 radiomics features and 13 clinical features. Kaplan-Meier analysis was used to estimate progression-free survival (PFS), and log-rank test was used to screen the significant features. Cox proportional hazards regression modal with forward stepwise feature selection was adopted to identify independent predictors of PFS. 24 radiomics features and 8 clinical features were found to be significantly associated with PFS in univariate analysis. Radiomics features HGZE-GLSZM-HLL-32 (p=0.0061, HR: 0.66, 95%CI: 0.49-0.89), as well as clinical features N-stage, M-stage, antibody VCA-IgA and platelet count (PLT) retained the independent prognostic significance for PFS in multivariate analysis. Overall, radiomics features can provide complementary prognostic information for NPC patients imaged with baseline 18F-FDG PET/CT compared to clinical features. © 2018 IEEE.

关键词： Multivariant analysis