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Mobile's millimeter-wave makeover: Wireless engineers long considered high frequencies worthless for cellular systems. They couldn't be more wrong

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IEEE Spectrum 2014年第9期51卷 34-58页

作者： Rappaport, Theodore Roh, Wonil Cheun, Kyungwhoon Vision and Image Processing Research Group Department of Systems Design Engineering University of Waterloo Waterloo ON Canada

People in real estate joke that there are only three things that matter in the business of buying and selling property: location, location, location. The same could be said for radio spectrum. The frequencies used for cellular communications have acquired the status of waterfront lots-highly coveted and woefully scarce. And like beach-home buyers in a bidding war, mobile operators must constantly jockey for these prime parcels, sometimes shelling out as much as tens of billions of dollars for just a small sliver of the electromagnetic pie. © 1964-2012 IEEE.

关键词： Location

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Adaptive regularized multichannel Blind deconvolution using alternating minimization

Adaptive regularized multichannel Blind deconvolution using ...

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IEEE International Advance Computing Conference, IACC

作者： Soniya James Vivek Maik Joonki Paik Department of Electronics and Communication The Oxford College of Engineering Bangalore India Image processing and Intelligent Systems Laboratory Chung-ang university Korea

ISBN: (纸本)9781479980482

Multichannel blind deconvolution is an ill posed problem where regularizers plays an important role. Adaptive regularization is used to obtain better quality restored image. This adds penalty weighted term along with image regularizer. The Isotropic TV image regularizers have chosen along with directional priors which preserves the over smoothing of the edges when compare to horizontal and vertical priors, thereby improving the Peak Signal to Noise Ratio(PSNR) of the reconstructed image. The Blind deconvolution problem can be solved using Alternating minimization algorithm as it is best suited for two unknown variables. The formulation of blind deconvolution can be l 1 regularized optimization and geometry can be l 2 . It results in hard optimization problem. The minimization step alternates between two sub optimization problems and this can be solve efficiently using Augmented Lagrangian method(ALM), where each iteration undergoes Bregman variable splitting or iterative method. This converted unconstrained problem in to constrained. This method can be applicable to medical images such as X Ray in order to reduce the amount of rays penetrating in to the body and to observe more details.

关键词： Minimization Deconvolution Optimization image restoration TV image reconstruction Convergence

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Author Correction: The challenge of mapping the human connectome based on diffusion tractography

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Nature communications 2019年第1期10卷 5059页

作者： Klaus H Maier-Hein Peter F Neher Jean-Christophe Houde Marc-Alexandre Côté Eleftherios Garyfallidis Jidan Zhong Maxime Chamberland Fang-Cheng Yeh Ying-Chia Lin Qing Ji Wilburn E Reddick John O Glass David Qixiang Chen Yuanjing Feng Chengfeng Gao Ye Wu Jieyan Ma Renjie He Qiang Li Carl-Fredrik Westin Samuel Deslauriers-Gauthier J Omar Ocegueda González Michael Paquette Samuel St-Jean Gabriel Girard François Rheault Jasmeen Sidhu Chantal M W Tax Fenghua Guo Hamed Y Mesri Szabolcs Dávid Martijn Froeling Anneriet M Heemskerk Alexander Leemans Arnaud Boré Basile Pinsard Christophe Bedetti Matthieu Desrosiers Simona Brambati Julien Doyon Alessia Sarica Roberta Vasta Antonio Cerasa Aldo Quattrone Jason Yeatman Ali R Khan Wes Hodges Simon Alexander David Romascano Muhamed Barakovic Anna Auría Oscar Esteban Alia Lemkaddem Jean-Philippe Thiran H Ertan Cetingul Benjamin L Odry Boris Mailhe Mariappan S Nadar Fabrizio Pizzagalli Gautam Prasad Julio E Villalon-Reina Justin Galvis Paul M Thompson Francisco De Santiago Requejo Pedro Luque Laguna Luis Miguel Lacerda Rachel Barrett Flavio Dell'Acqua Marco Catani Laurent Petit Emmanuel Caruyer Alessandro Daducci Tim B Dyrby Tim Holland-Letz Claus C Hilgetag Bram Stieltjes Maxime Descoteaux Division of Medical Image Computing German Cancer Research Center (DKFZ) Heidelberg 69120 Germany. k.maier-hein@dkfz.de. Division of Medical Image Computing German Cancer Research Center (DKFZ) Heidelberg 69120 Germany. Sherbrooke Connectivity Imaging Lab (SCIL) Université de Sherbrooke Sherbrooke QC J1K 0A5 QC Canada. Department of Intelligent Systems Engineering School of Informatics and Computing Indiana University Bloomington IN 47408 USA. Krembil Research Institute University Health Network Toronto Canada M5G 2C4. Department of Neurological Surgery University of Pittsburgh School of Medicine Pittsburgh PA 15213 USA. IMT-Institute for Advanced Studies Lucca 55100 Italy. Department of Diagnostic Imaging St. Jude Children's Research Hospital Memphis TN 38105 USA. University of Toronto Institute of Medical Science Toronto Canada M5S 1A8. Institute of Information Processing and Automation Zhejiang University of Technology Hangzhou 310023 Zhejiang China. United Imaging Healthcare Co Shanghai 201807 China. Shanghai Advanced Research Institute Shanghai 201210 China. Laboratory of Mathematics in Imaging Harvard Medical School Boston MA 02215 USA. Center for Research in Mathematics Guanajuato 36023 Mexico. PROVIDI Lab Image Sciences Institute University Medical Center Utrecht Utrecht 3508 The Netherlands. Cardiff University Brain Research Imaging Centre School of Psychology Cardiff University Maindy Road Cardiff CF24 4HQ UK. Department of Radiology University Medical Center Utrecht Utrecht 3508 The Netherlands. Centre de recherche institut universitaire de geriatrie de Montreal (CRIUGM) Université de Montréal Montreal QC Canada H3W 1W5. Sorbonne Universités UPMC Univ Paris 06 CNRS INSERM Laboratoire d'Imagerie Biomédicale (LIB) 75013 Paris France. Center for Advanced Research in Sleep Medicine Hôpital du Sacré-Coeur de Montréal Montreal Canada H4J 1C5. Neuroimaging Unit Institute of Bioimaging and Molecular Physiology (IBFM) Nat

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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Shifted nondiffractive Bessel beams

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Physical Review A 2015年第5期91卷 053840-053840页

作者： Alexey A. Kovalev Victor V. Kotlyar Alexey P. Porfirev Laser Measurements Laboratory Image Processing Systems Institute Russian Academy of Sciences 151 Molodogvardejskaya street Samara Russia 443001 and Technical Cybernetics sub-department S.P. Korolyov Samara State Aerospace University (National Research University) 34 Moskovskoye shosse Samara Russia 443086

Nondiffractive Bessel beams are well known to have infinite energy and infinite orbital angular momentum (OAM). However, when normalized to unity of energy, their OAM is finite. In this work, we derive an analytical relationship for calculating the normalized OAM of the superposition of off-axis Bessel beams characterized by the same topological charge. We show that if the constituent beams of the superposition have real-valued weight coefficients, the total OAM of the superposition of the Bessel beams equals that of an individual nonshifted Bessel beam. This property enables generating nondiffractive beams with different intensity distributions but identical OAM. The superposition of a set of identical Bessel beams centered on an arbitrary-radius circle is shown to be equivalent to an individual constituent Bessel beam put in the circle center. As a result of a complex shift of the Bessel beam, the transverse intensity distribution and OAM of the beam are also shown to change. We show that, in the superposition of two or more complex-shifted Bessel beams, the OAM may remain unchanged, while the intensity distribution is changed. Numerical simulation is in good agreement with theory.

关键词： BESSEL beams OPTICAL diffraction FORCE & energy ANGULAR momentum (Mechanics) SUPERPOSITION (Optics) NUMERICAL analysis

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A low resolution multi-camera system for person tracking

A low resolution multi-camera system for person tracking

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作者： Eldib, Mohamed Bo, Nyan Bo Deboeverie, Francis Nino, Jorge Guan, Junzhi Van De Velde, Samuel Steendam, Heidi Aghajan, Hamid Philips, Wilfried Department of Telecommunications and Information Processing Ghent University-iMinds Belgium Image Processing and Interpretation-Vision Systems United States Ambient Intelligence Research Lab Stanford University United States

ISBN: (纸本)9781479957514

The current multi-camera systems have not studied the problem of person tracking under low resolution constraints. In this paper, we propose a low resolution sensor network for person tracking. The network is composed of cameras with a resolution of 30×30 pixels. The multi-camera system is used to evaluate probability occupancy mapping and maximum likelihood trackers against ground truth collected by ultra-wideband (UWB) testbed. Performance evaluation is performed on two video sequences of 30 minutes. The experimental results show that maximum likelihood estimation based tracker outperforms the state-of-the-art on low resolution cameras. © 2014 IEEE.

关键词： Maximum likelihood estimation

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Motion control and fall detection of intelligent cane robot

Springer Tracts in Advanced Robotics

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Springer Tracts in Advanced Robotics 2015年 106卷 317-337页

作者： Fukuda, Toshio Huang, Jian Di, Pei Sekiyama, Kosuge Key Laboratory of Image Processing and Intelligent Control School of Automation Huazhong University of Science and Technology No. 1037 Luoyu Road Wuhan Hubei430074 China Department of Micro-Nano Systems Engineering Nagoya University Furo-cho Chikusa-ku Nagoya464-8603 Japan

An intelligent cane robot was designed for aiding the elderly and handicapped people walking. The robot consists of a stick, a group of sensors and an omni-directional basis driven by three Swedish wheels. Multiple sensors were used to recognize the user’s "walking intention", which is quantitatively described by a new concept called intentional direction (ITD). Based on the guidance of filtered ITD, a novel intentionbased admittance motion control (IBAC) scheme was proposed for the cane robot. The experiment results demonstrated that the user feels more natural and comfortable when walking with the assistance of cane robot controlled by the IBAC strategy. To detect the fall of user, a detection method based on Dubois possibility theory was proposed using the combined sensor information from force sensors and a laser ranger finder (LRF) fixed on the cane robot. The human fall model was represented in a two-dimensional space, where the relative position between the Zero- Moment-Point (ZMP) and the center of support triangle was utilized as a significant feature. The effectiveness of proposed fall detection method was also confirmed by experiments. © Springer International Publishing Switzerland 2015.

关键词： Motion control

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2D-PCA shape models: Application to 3D reconstruction of the human teeth from a single image

2D-PCA shape models: Application to 3D reconstruction of the...

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3rd International MICCAI Workshop on Medical Computer vision, MCV 2013

作者： Abdelrehim, Aly S. Farag, Aly A. Shalaby, Ahmed M. El-Melegy, Moumen T. Computer Vision and Image Processing Laboratory University of Louisville Louisville KY 40292 United States Electrical Engineering Department Assiut University Assiut 71516 Egypt

ISBN: (纸本)9783319055299

Accurate modeling of human teeth is mandatory for many reasons. Some of them are (1) Providing comfort to patients during mold process, and (2) Enhancing the accuracy level for oral orthodontist and dental care personnel. Shape from Shading (SFS) proved to be of great help in this problem, considering the fact that human tooth surface is textureless. In this paper, we address the problem of 3D tooth reconstruction, and improve the current algorithms. The approached developed in this paper reconstructs the teeth from single image shading with 2D-PCA shape priors that have more sophisticated reflectance model. Oren-Nayar-Wolff model was used for modeling the surface reflectance. This formulation uses shape priors as got from a set of training CT scans of real human teeth. Our experiments show promising quantitative results, which builds the infrastructure for having an optical based approach that accounts for inexpensive and radiationless human tooth reconstruction. © 2014 Springer International Publishing Switzerland.

关键词： Computerized tomography

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Global Bounded Consensus of General Nonidentical Networks With Distributed Time-Delays

Global Bounded Consensus of General Nonidentical Networks Wi...

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IEEE Annual Conference on Decision and Control

作者： Xiuxian Li Housheng Su Chanying Li Zheng Wang Michael Z. Q. Chen Department of Mechanical Engineering The University of Hong Kong Pokfulam Hong Kong School of Automation Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 PR China National Center for Mathematics and Interdisciplinary Sciences Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9781479978878

In this paper, global bounded consensus problem of general nonidentical networks with nonlinear dynamics and distributed time-delays is investigated, in which the distributed time-delays are distinct from each other. The global consensus exists in the sense of boundedness since complete consensus does not often exist in the nonidentical case. With the aid of constructing a Lyapunov-Krasovskii functional and utilizing the technique of integral partitioning, some sufficient delay-dependent conditions are derived to ensure that global bounded consensus is achieved ultimately. Finally, effectiveness of the theoretical result is illustrated by a numerical example.

关键词： Bounded Nonlinear Dynamics numerical example Distribute Automatic incident detection Distinct

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A low resolution multi-camera system for person tracking

A low resolution multi-camera system for person tracking

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IEEE International Conference on image processing

作者： Mohamed Eldib Nyan Bo Bo Francis Deboeverie Jorge Nino Junzhi Guan Samuel Van de Velde Heidi Steendam Hamid Aghajan Wilfried Philips Image Processing and Interpretation-Vision Systems Department of Telecommunications and Information Processing Ghent University-iMinds Belgium Ambient Intelligence Research Lab Stanford University USA

关键词： Cameras image resolution Correlation Maximum likelihood detection Maximum likelihood estimation Video sequences Tracking

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