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arXiv 2020年

作者： Abdar, Moloud Pourpanah, Farhad Hussain, Sadiq Rezazadegan, Dana Liu, Li Ghavamzadeh, Mohammad Fieguth, Paul Cao, Xiaochun Khosravi, Abbas Rajendra Acharya, U. Makarenkov, Vladimir Nahavandi, Saeid Deakin University Australia College of Mathematics and Statistics Guangdong Key Lab. of Intelligent Information Processing Shenzhen University Shenzhen518060 China Dibrugarh University Dibrugarh India Department of Computer Science and Software Engineering Swinburne University of Technology Melbourne Australia Center for Machine Vision and Signal Analysis University of Oulu Oulu Finland Google research United States Department of Systems Design Engineering University of Waterloo Waterloo Canada State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences Beijing China Department of Electronics and Computer Engineering Ngee Ann Polytechnic Clementi Singapore Department of Computer Science University of Quebec in Montreal MontrealQC Canada

—Uncertainty quantification (UQ) plays a pivotal role in the reduction of uncertainties during both optimization and decision making, applied to solve a variety of real-world applications in science and engineering. Bayesian approximation and ensemble learning techniques are two of the most widely-used UQ methods in the literature. In this regard, researchers have proposed different UQ methods and examined their performance in a variety of applications such as computer vision (e.g., self-driving cars and object detection), image processing (e.g., image restoration), medical image analysis (e.g., medical image classification and segmentation), natural language processing (e.g., text classification, social media texts and recidivism risk-scoring), bioinformatics, etc. This study reviews recent advances in UQ methods used in deep learning, investigates the application of these methods in reinforcement learning, and highlight the fundamental research challenges and directions associated with the UQ field. Copyright © 2020, The Authors. All rights reserved.

关键词： Image segmentation

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A Fast Proportionate RLS Adaptive Equalization for Underwater Acoustic Communications

A Fast Proportionate RLS Adaptive Equalization for Underwate...

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OCEANS - Europe

作者： Zhen Qin Jun Tao Feng Tong Hongtao Zhang Fengzhong Qu Xiao Han Key Laboratory of Underwater Acoustic Signal Processing of the Ministry of Education School of Information Science and Engineering Southeast University Nanjing China State Key Lab. of Acoustics Institute of Acoustics Chinese Academy of Sciences Beijing China College of Ocean and Earth Sciences Xiamen University Xiamen China Hangzhou Appiled Acoustics Research Institute Hangzhou China Key Laboratory of Ocean Observation-Imaging Testbed of Zhejiang Province Zhejiang University Zhoushan China Acoustic Science and Technology Laboratory Harbin Engineering University Harbin China

In this paper, a low-complexity recursive least squares (RLS) type sparse direct adaptive equalizer (DAE) is proposed for multiple-input multiple-output (MIMO) underwater acoustic (UWA) communications. The underlying proportionate RLS (PRLS) adaptive filter algorithm is motivated by the idea of proportionate updating (PU) originated in the improved proportionate normalized least mean squares (IPNLMS) adaptive filter scheme. To overcome the high complexity of the PRLS that is quadratic in the filter size, a fast implementation is developed in a way similar to the design of the stable fast transversal filter (SFTF) as a low-complexity approximation of the standard RLS adaptive filter algorithm. The resulting fast version of the PRLS is named the proportionate SFTF (PSFTF). The PSFTF is then adopted to update coefficients of a linear equalizer (LE), which was tested by experimental data collected in at-sea UWA communication trials. Experimental results showed the PSFTFDAE achieves faster convergence and better performance than existing SFTF-DAE and RLS-DAE.

关键词： Complexity theory MIMO communication Standards Equalizers Channel estimation Underwater acoustics signal processing algorithms

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AIROGS: ARTIFICIAL INTELLIGENCE FOR ROBUST GLAUCOMA SCREENING CHALLENGE

arXiv

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arXiv 2023年

作者： De Vente, Coen Vermeer, Koenraad A. Jaccard, Nicolas Wang, He Sun, Hongyi Khader, Firas Truhn, Daniel Aimyshev, Temirgali Zhanibekuly, Yerkebulan Le, Tien-Dung Galdran, Adrian Ballester, Miguel Ángel González Carneiro, Gustavo Devika, R.G. Hrishikesh, P.S. Puthussery, Densen Liu, Hong Yang, Zekang Kondo, Satoshi Kasai, Satoshi Wang, Edward Durvasula, Ashritha Heras, Jónathan Zapata, Miguel Ángel Araújo, Teresa Aresta, Guilherme Bogunović, Hrvoje Arikan, Mustafa Lee, Yeong Chan Cho, Hyun Bin Choi, Yoon Ho Qayyum, Abdul Razzak, Imran Van Ginneken, Bram Lemij, Hans G. Sánchez, Clara I. Group Informatics Institute Universiteit Van Amsterdam Noord-Holland Amsterdam Netherlands The Department of Biomedical Engineering and Physics Amsterdam Umc Locatie Amc Noord-Holland Amsterdam Netherlands Department of Radiology and Nuclear Medicine Radboudumc Gelderland Nijmegen Netherlands The Rotterdam Ophthalmic Institute Rotterdam Eye Hospital Rotterdam Netherlands Project Orbis International Inc. New York United States The Peking Union Medical College Hospital Beijing China The Xuanwu Hospital Capital Medical University Beijing100053 China The Tsinghua University Beijing China The Department of Diagnostic and Interventional Radiology University Hospital Aachen Aachen Germany Cmc Technologies Llp Nur-Sultan Kazakhstan Kbc Belgium Universitat Pompeu Fabra Barcelona Spain The Australian Institute for Machine Learning Aiml University of Adelaide Australia Icrea Barcelona Spain The Centre for Vision Speech and Signal Processing University of Surrey United Kingdom The College of Engineering Trivandrum India Founding Minds Software India The Institute of Computing Technology Chinese Academy of Sciences China The Muroran Institute of Technology Japan The Niigata University of Health and Welfare Japan The Schulich School of Medicine and Dentistry University of Western Ontario London Canada The Department of Mathematics and Computer Science University of la Rioja Spain Hospital Vall Hebron Passeig Roser 126 Sant Cugat del Vallès Barcelona08195 Spain UPRetina Barcelona Spain The Christian Doppler Laboratory for Artificial Intelligence in Retina Department of Ophthalmology and Optometry Medical University of Vienna Vienna Austria The Institute of Ophthalmology University College London London United Kingdom The Research Institute for Future Medicine Samsung Medical Center Seoul Korea Republic of Sungkyunkwan University Samsung Medical Center Seoul Korea Republic of The Department of Artificial Intelligence and Informatics Mayo Clinic Jacks

The early detection of glaucoma is essential in preventing visual impairment. Artificial intelligence (AI) can be used to analyze color fundus photographs (CFPs) in a cost-effective manner, making glaucoma screening more accessible. While AI models for glaucoma screening from CFPs have shown promising results in laboratory settings, their performance decreases significantly in realworld scenarios due to the presence of out-of-distribution and low-quality images. To address this issue, we propose the Artificial Intelligence for Robust Glaucoma Screening (AIROGS) challenge. This challenge includes a large dataset of around 113,000 images from about 60,000 patients and 500 different screening centers, and encourages the development of algorithms that are robust to ungradable and unexpected input data. We evaluated solutions from 14 teams in this paper, and found that the best teams performed similarly to a set of 20 expert ophthalmologists and optometrists. The highest-scoring team achieved an area under the receiver operating characteristic curve of 0.99 (95% CI: 0.98-0.99) for detecting ungradable images on-the-fly. Additionally, many of the algorithms showed robust performance when tested on three other publicly available datasets. These results demonstrate the feasibility of robust AI-enabled glaucoma screening. Copyright © 2023, The Authors. All rights reserved.

关键词： Diagnosis

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T/l-shaped zeroth-order resonators loaded microstrip antenna with enhanced bandwidth for wireless applications

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Progress In Electromagnetics Research C 2018年 80卷 157-166页

作者： Sun, Kai Peng, Lin Li, Quan Jiang, Xing The Guangxi Key Laboratory of Wireless Wideband Communication and Signal Processing Guilin University of Electronic Technology GuilinGuangxi541004 China Guangxi Experiment Center of Information Science GuilinGuangxi541004 China

New zeroth-order resonators (ZORs) are utilized as parasitic elements to enhance a microstrip antenna’s bandwidth. By utilizing mushroom T/L shaped resonators, extra resonances are generated. Then, by merging the resonances of the microstrip antenna and the T/L shaped resonators, a wideband antenna is obtained to cover the 5.15–5.35 GHz wireless local area network (WLAN) band. As the ZORs are embedded in the patch of the microstrip antenna, the usages of the parasitic elements do not increase the antenna size. Moreover, as one ZOR resonance is lower than the microstrip patch resonance, a compact antenna is realized. The patch size is decreased from 0.27λc ×0.42λc ×0.027λc of the reference microstrip antenna (RMA) to 0.25λc ×0.40λc ×0.026λc of the proposed ZOR based microstrip antenna, where λc is the wavelength of their corresponding lower cutoff frequencies. The proposed antenna was fabricated and measured. The simulated and measured −10 dB impedance bands of the proposed antenna are 5.06–5.40 GHz and 5.07–5.42 GHz, respectively. And, its bandwidth increases 70% compared to the RMA. The simulated and measured patterns are stable in the whole operating band. The gains of 4.73 dBi and 4.24 dBi are measured at the ZOR modes, and 7.88 dBi is measured at the microstrip patch mode. © 2018, Electromagnetics Academy. All rights reserved.

关键词： Microstrip antennas

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Discovering Temporal User Interest on Twitter by Using Semantic Based Dynamic Interest Finding Model(TUT) 2nd

Discovering Temporal User Interest on Twitter by Using Seman...

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2017 IEEE 2nd Information technology, Networking, Electronic and Automation Control Conference (ITNEC 2017)

作者： Rashid Abbasi Gohar Rehman Jia lee Farhad Muhammad Riaz Bin Luo School of Computer Science and Technology Anhui University College of Computer Science Chongqing University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University

ISBN: (纸本)9781509064151;9781509064144

Social media systems are very popular in today's dynamic web. One of the famous social media systems is Twitter, in which peoples used to share their personal ideas about current issues with their friends. This work focuses on the problem of discovering a user's interest over time on twitter. Previous approaches have used to model the user topic of interest on twitter by building the profile of the users, that contain the words which can be used the user in his or her conversions with other users, but on twitter users used the noisy words which does not represent the correct topics or topic related to interest. This model has extended by a novel framework by using twitter user model. This model uses the latent topic variable to indicate the relatedness of the topic with any user. In this work, we propose a Temporal User Topic(TUT) approach which can consider the text of tweet by any user and time of the tweet. The proposed approach is used to discover topically related Users for different time periods. We also show how the interests and relationships of these users are changeovers a time period.

关键词： Topic Model User Interest Twitter Twitter-User Model Social Network Time Topic Modeling

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Mining and Harvesting High Quality Topical Resources from the Web

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Chinese Journal of Electronics 2016年第1期25卷 48-57页

作者： ZHAO Wei GUAN Ziyu CAO Zhengwen LIU Zheng National Laboratory of Radar Signal Processing Xidian University College of Information and Technology Northwest University of China

Focused crawlers aim to effectively prioritize uncrawled URLs to harvest relevant pages while avoiding irrelevant ones. In practice, harvesting high quality topical Web resources is more important due to the explosion of Web information. Our study shows that the popular focused crawling strategy cannot achieve this *** this paper we develop a new focused crawler, namely On-line topical quality estimation(OTQE), which intelligently evaluates the topical quality of uncrawled pages by the observed link and content evidences and prioritize their URLs accordingly. The new crawler is scalable and requires fewer additional resources to do link-based analysis. The experimental results on crawling 3.6 million Web pages demonstrate the advantages of our proposed method over traditional focused crawlers.

关键词： Focused crawling Topical crawlers Clas sification Open directory project

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A Novel Level Set Model Originated from Fuzzy Connectedness Guided Initial Contours

A Novel Level Set Model Originated from Fuzzy Connectedness ...

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International Conference on Image, Vision and Computing (ICIVC)

作者： Yiwei Liu Peirui Bai Chang Li Yue Zhao School of Electronic Communications and Physics Shandong University of Science and Technology Qingdao China Chongqing Key Laboratory of Signal and Information Processing Chongqing University of Posts and Telecommunications Chongqing China

ISBN: (纸本)9781538649923

Level set models are widely used in the image segmentation field. However, the sensitivity of the initial contours and the manual adjustment of the controlling parameters have limited the segmentation performance. To effectively solve this problem, a novel level set model utilizing both intensity and spatial information is proposed in this paper. Firstly, the fuzzy connectedness (FC) algorithm is applied to obtain the appropriate initial contours, and as a result the complexity and computation cost of building initial contours is reduced. Secondly, based on the morphological characteristics of the initial contours and the parameters of fuzzy connectedness, several equations are proposed to automatically estimate the controlling parameters of the level set evolution and avoid human intervention. Finally, the region-scalable fitting (RSF) model is adopted to evolve and obtain the final robust segmentation results. The efficiency and accuracy of the model proposed in this paper is verified by comparing the three quantitative indexes of time, Dice similarity coefficient (DSC) and peak signal to noise ratio (PSNR) with four different initialized level set models.

关键词： Level set Image segmentation Mathematical model Fitting Computational modeling Adaptation models Nonhomogeneous media

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Two New Closed Form Approximate Maximum Likelihood Location Methods Based on Time Difference of Arrival Measurements

Two New Closed Form Approximate Maximum Likelihood Location ...

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2018 International Conference on Computer science, Electronics and Communication Engineering（CSECE2018）

作者： Wanchun Li Qiu Tang Yingxiang Li Guobin Qian School of Electronic Engineering University of Electronic Science and Technology of China School of Communication Engineering Chengdu University of Information Technology Meteorological information and Signal Processing Key Laboratory of Sichuan Higher Education Institutes

ISBN: (纸本)9781510862593

In this paper, we propose two new closed form approximate maximum likelihood location methods via time difference of arrival(TDOA) measurements to determine the location of a target. For both two methods, an initial estimation is acquired by least square method in the first step. Then, supposing that the statistical structure of measurement noise are already known, the maximum likelihood function is derived. At last, for method one, we use first order Taylor expand at the initial point to approximate the residual error for nonlinear measurement equation and substitute it into the maximum likelihood function. While for method two, we use second order Taylor expand at the initial point to approximate the maximum likelihood function. At last, we derive the closed-form solution to both of the methods respectively. The computational complexity of our methods and AML method is derived and we analyze the performance of our two methods. The simulation results show that our methods are more accurate because our methods based on maximum likelihood function and have low computational complexity because we iterate only once.

关键词： TDOA location maximum likelihood closed form solution performance analysis

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Object tracking by reconstruction with view-specific discriminative correlation filters

arXiv

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arXiv 2018年

作者： Kart, Uǧur Lukežič, Alan Kristan, Matej Kämäräinen, Joni-Kristian Matas, Jiří Laboratory of Signal Processing Tampere University of Technology Finland Faculty of Computer and Information Science University of Ljubljana Slovenia Faculty of Electrical Engineering Czech Technical University in Prague Czech Republic

Standard RGB-D trackers treat the target as an in ently 2D structure, which makes modelling appear changes related even to simple out-of-plane rotation h challenging. We address this limitation by proposi novel long-term RGB-D tracker - Object Tracking by construction (OTR). The tracker performs online 3D t reconstruction to facilitate robust learning of a set of v specific discriminative correlation filters (DCFs). Th reconstruction supports two performance-enhancing features: (i) generation of accurate spatial support for constrained DCF learning from its 2D projection and (ii) point-cloud based estimation of 3D pose change for selection and storage of view-specific DCFs which are used to robustly localize the target after out-of-view rotation or heavy occlusion. Extensive evaluation of OTR on the challenging Princeton RGB-D tracking and STC Benchmarks shows it outperforms the state-of-the-art by a large margin. Copyright © 2018, The Authors. All rights reserved.

关键词： Machine learning

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A novel clustering method based on density peaks and its validation by channel measurement 12

A novel clustering method based on density peaks and its val...

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12th European Conference on Antennas and Propagation, EuCAP 2018

作者： Xue, Hanqing Tian, Lei Zhang, Yuxiang Wang, Chao Zhang, Jianhua Li, Wei Wei, Hewen Key Lab of Universal Wireless Communications Ministry of Education China State Key Lab of Networking and Switching Technology Beijing University of Posts and Telecommunications P. O. Box 92 Beijing100876 China Department of Electrical Engineering Northern Illinois University DeKalbIL60115 United States National key laboratory of science and technology on blind signal processing Chengdu Sichuan610041 China

ISBN: (纸本)9781785617911

In this paper, cluster centers are defined as local maxima in the density which is called density peaks. We use an algorithm based on density peaks to cluster multipath components (MPCs) whose parameters are estimated by the space-alternating generalized expectation-maximization (SAGE) algorithm. To validate its performance, we apply it to the data from a channel measurement in an indoor scenario at 28 GHz and compare it to the widely used KPowerMeans algorithm with the same distance metric of multiple component distance (MCD). Through the results, we find it can cluster MPCs more accurately validated by Calinski-Harabasz (CH) and Davies-Bouldin (DB) indices. More importantly, it overcomes the shortcoming of setting the number of clusters manually because we can determine the cluster centers automatically. Besides, the efficiency of DP clustering is far superior to KPowerMeans because what it needs is only a distance matrix and we only need to compute it once. At the end, statistical analysis of clusters are presented to provide insights in channel modeling of millimeter wave. © Institution of Engineering and *** Rights Reserved.

关键词： Millimeter waves

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