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arXiv 2019年

作者： Bilic, Patrick Christ, Patrick Li, Hongwei Bran Vorontsov, Eugene Ben-Cohen, Avi Kaissis, Georgios Szeskin, Adi Jacobs, Colin Mamani, Gabriel Efrain Humpire Chartrand, Gabriel Lohöfer, Fabian Holch, Julian Walter Sommer, Wieland Hofmann, Felix Hostettler, Alexandre Lev-Cohain, Naama Drozdzal, Michal Amitai, Michal Marianne Vivanti, Refael Sosna, Jacob Ezhov, Ivan Sekuboyina, Anjany Navarro, Fernando Kofler, Florian Paetzold, Johannes C. Shit, Suprosanna Hu, Xiaobin Lipková, Jana Rempfler, Markus Piraud, Marie Kirschke, Jan Wiestler, Benedikt Zhang, Zhiheng Hülsemeyer, Christian Beetz, Marcel Ettlinger, Florian Antonelli, Michela Bae, Woong Bellver, Míriam Bi, Lei Chen, Hao Chlebus, Grzegorz Dam, Erik B. Dou, Qi Fu, Chi-Wing Georgescu, Bogdan Giró-I-Nieto, Xavier Gruen, Felix Han, Xu Heng, Pheng-Ann Hesser, Jürgen Moltz, Jan Hendrik Igel, Christian Isensee, Fabian Jäger, Paul Jia, Fucang Kaluva, Krishna Chaitanya Khened, Mahendra Kim, Ildoo Kim, Jae-Hun Kim, Sungwoong Kohl, Simon Konopczynski, Tomasz Kori, Avinash Krishnamurthi, Ganapathy Li, Fan Li, Hongchao Li, Junbo Li, Xiaomeng Lowengrub, John Ma, Jun Maier-Hein, Klaus Maninis, Kevis-Kokitsi Meine, Hans Merhof, Dorit Pai, Akshay Perslev, Mathias Petersen, Jens Pont-Tuset, Jordi Qi, Jin Qi, Xiaojuan Rippel, Oliver Roth, Karsten Sarasua, Ignacio Schenk, Andrea Shen, Zengming Torres, Jordi Wachinger, Christian Wang, Chunliang Weninger, Leon Wu, Jianrong Xu, Daguang Yang, Xiaoping Yu, Simon Chun-Ho Yuan, Yading Yue, Miao Zhang, Liping Cardoso, Jorge Bakas, Spyridon Braren, Rickmer Heinemann, Volker Pal, Christopher Tang, An Kadoury, Samuel Soler, Luc van Ginneken, Bram Greenspan, Hayit Joskowicz, Leo Menze, Bjoern Department of Informatics Technical University of Munich Germany Department of Quantitative Biomedicine University of Zurich Switzerland Ecole Polytechnique de Montréal Canada Department of Medical Imaging Radboud University Medical Center Nijmegen Netherlands Department of Biomedical Engineering Tel-Aviv University Israel Germany Pattern Analysis and Learning Group Department of Radiation Oncology Heidelberg University Hospital Heidelberg Germany Philips Research China Philips China Innovation Campus Shanghai China School of Biomedical Engineering & Imaging Sciences King0s College London London United Kingdom Institute for AI in Medicine Technical University of Munich Germany Department of Computer Science Guangdong University of Foreign Studies China Institute for diagnostic and interventional radiology Klinikum rechts der Isar Technical University of Munich Germany Institute for Diagnostic and Interventional Neuroradiology Klinikum Rechts der Isar Technical University of Munich Germany Department of Hepatobiliary Surgery The Affiliated Drum Tower Hospital Nanjing University Medical School China Department of Computing Imperial College London London United Kingdom Institute for Tissue Engineering and Regenerative Medicine Helmholtz Zentrum München Neuherberg Germany Brigham and Women's Hospital Harvard Medical School United States School of Computer Science and Engineering The Hebrew University of Jerusalem Israel University of Pennsylvania PA United States Pte. Ltd. Singapore Medical Imaging and Reconstruction Lab Department of Engineering Design Indian Institute of Technology Madras India Sensetime Shanghai China Department of Radiology Perelman School of Medicine University of Pennsylvania United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PA United States Co. Ltd China MontréalQC Canada Department of Radiology Radiation Oncology and Nuclear Medicine University of Montréal

In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS), which was organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI) 2017 and the International Conferences on Medical Image Computing and computer-Assisted Intervention (MICCAI) 2017 and 2018. The image dataset is diverse and contains primary and secondary tumors with varied sizes and appearances with various lesion-to-background levels (hyper-/hypo-dense), created in collaboration with seven hospitals and research institutions. Seventy-five submitted liver and liver tumor segmentation algorithms were trained on a set of 131 computed tomography (CT) volumes and were tested on 70 unseen test images acquired from different patients. We found that not a single algorithm performed best for both liver and liver tumors in the three events. The best liver segmentation algorithm achieved a Dice score of 0.963, whereas, for tumor segmentation, the best algorithms achieved Dices scores of 0.674 (ISBI 2017), 0.702 (MICCAI 2017), and 0.739 (MICCAI 2018). Retrospectively, we performed additional analysis on liver tumor detection and revealed that not all top-performing segmentation algorithms worked well for tumor detection. The best liver tumor detection method achieved a lesion-wise recall of 0.458 (ISBI 2017), 0.515 (MICCAI 2017), and 0.554 (MICCAI 2018), indicating the need for further research. LiTS remains an active benchmark and resource for research, e.g., contributing the liver-related segmentation tasks in http://***/. In addition, both data and online evaluation are accessible via ***. © 2019, CC BY-NC-ND.

关键词： Deep learning

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A green wireless powered sensor network: An experimental approach 18

A green wireless powered sensor network: An experimental app...

引用

18th Mediterranean Electrotechnical Conference, MELECON 2016

作者： Kyprianou, Christos Psomas, Constantinos Krikidis, Ioannis KIOS Research Center for Intelligent Systems and Networks Department of Electrical and Computer Engineering University of Cyprus Cyprus

ISBN: (纸本)9781509000579

This paper presents an experimental study of a green wireless powered communication network (WPCN), where sensors with wireless power transfer (WPT) capabilities are located at known positions and an energy transmitter (ETx) is employed to wirelessly power the uplink between the sensors and the access point (AP). By monitoring and measuring the charging time that the sensors require to power their operations, the ETx is turned on and off accordingly for a certain period of time in order to keep the packet transmission rate at a desired constant value. We consider a static and dynamic approach for the measurements and repeat the experiments for various packet rate constraints and different distances between the sensors and the ETx. Our results show that the power consumption of our smart ETx can achieve power savings of 80% compared to an ETx which operates continuously. © 2016 IEEE.

关键词： Wireless sensor networks

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Methods and measurements to compare men against machines

Methods and measurements to compare men against machines

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Human Vision and Electronic Imaging 2017, HVEI 2017

作者： Wichmann, Felix A. Janssen, David H.J. Geirhos, Robert Aguilar, Guillermo Schütt, Heiko H. Maertens, Marianne Bethge, Matthias Neural Information Processing Group University of Tübingen Germany Bernstein Center for Computational Neuroscience Tübingen Germany Max Planck Institute for Intelligent Systems Tübingen Germany Faculty of Computer Science and Electrical Engineering TU Berlin Germany Bernstein Center for Computational Neuroscience Berlin Germany Department of Psychology University of Potsdam Germany Centre for Integrative Neuroscience University of Tübingen Germany

Recent advances in computational models in vision science have considerably furthered our understanding of human visual perception. At the same time, rapid advances in convolutional deep neural networks (DNNs) have resulted in computer vision models of object recognition which, for the first time, rival human object recognition. Furthermore, it has been suggested that DNNs may not only be successful models for computer vision, but may also be good computational models of the monkey and human visual systems. The advances in computational models in both vision science and computer vision pose two challenges in two different and independent domains: First, because the latest computational models have much higher predictive accuracy, and competing models may make similar predictions, we require more human data to be able to statistically distinguish between different models. Thus we would like to have methods to acquire trustworthy human behavioural data fast and easy. Second, we need challenging experiments to ascertain whether models show similar input-output behaviour only near "ceiling" performance, or whether their performance degrades similar to human performance: only then do we have strong evidence that models and human observers may be using similar features and processing strategies. In this paper we address both challenges. © 2017, Society for Imaging Science and Technology.

关键词： Deep neural networks

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Adaptive noise cancellation using q-LMS

Adaptive noise cancellation using q-LMS

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International Conference on Innovations in electrical engineering and Computational Technologies (ICIEECT)

作者： M. Arif I. Naseem M. Moinuddin Saba S. Khan Malik M. Ammar Electrical Engineering Department Karachi Institute of Economics and Technology Karachi Pakistan Center of Excellence in Intelligent Engineering Systems (CEIES) King Abdulaziz University Jeddah Saudi Arabia Computer Engineering Department Chosun University Gawangju South Korea

ISBN: (纸本)9781509033119

When a signal is attenuated by some interference or additive noise, adaptive filters provide best solution for the recovery of such signals. Based on adaptive filtering several techniques (algorithms) have been developed in the literature. Due to simplicity, stability, low computational cost and better efficiency, Least Mean Square (LMS) algorithm attract many researchers in this regards. In this paper, a variant of LMS algorithm named q-Least Mean Square (q-LMS) algorithm is investigated for noise cancellation scenario. Moreover, an automatic methodology is adopted for time varying q parameter through which q parameter can adjust itself to get better efficiency and minimize the steady state error. The efficiency of the adopted algorithm is compared with the most widely used (LMS) algorithm by using MATLAB simulations.

关键词： Noise cancellation Speech Steady-state Standards Adaptation models Simulation Adaptive filters

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DSB-SEIs: A deduplicating secure backup system with encryption intensity selection 4

DSB-SEIs: A deduplicating secure backup system with encrypti...

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4th Annual ACM PODC Workshop on Distributed Cloud Computing, DCC 2016

作者： Aman, Mortada A. Cetinkaya, Egemen K. Department of Electrical and Computer Engineering Japan Intelligent Systems Center Missouri University of Science and Technology RollaMO65409 United States

ISBN: (纸本)9781450342209

Cloud computing is an emerging service that enables users to store and manage their data easily at a low cost. We propose a Deduplicating Secure Backup System with Encryption Intensity Selection (DSB-SEIS) that combines features to amend security and performance of cloud-based backup services. Our scheme introduces the concept of encryption intensity selection to cloud backup systems, which allows users to select the encryption intensity of their files. We also combine features such as deduplication, assured deletion, and multi-aspect awareness to further enhance our scheme. The DSB-SEIS performance is measured over an OpenStack cloud installed on CloudLab resources demonstrating that DSB-SEIS can improve the backup service. © 2016 ACM.

关键词： Cryptography

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Where Does AlphaGo Go: From Church-Turing Thesis to AlphaGo Thesis and Beyond

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IEEE/CAA Journal of Automatica Sinica 2016年第2期3卷 113-120页

作者： Fei-Yue Wang Jun Jason Zhang Xinhu Zheng Xiao Wang Yong Yuan Xiaoxiao Dai Jie Zhang Liuqing Yang IEEE the State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences (SKL-MCCS CASIA) Research Center of Computational Experiments and Parallel Systems The National University of Defense Technology the Department of Electrical and Computer Engineering Ritchie School of Engineering and Computer Science University of Denver the Department of Computer Science and Engineering University of Minnesota the Qingdao Academy of Intelligent Industries (QAII) Qingdao Shandong China and SKL-MCCS CASIA the Department of Electrical and Computer Engineering Colorado State University

An investigation on the impact and significance of the AlphaGo vs. Lee Sedol Go match is conducted, and concludes with a conjecture of the AlphaGo Thesis and its extension in accordance with the Church-Turing Thesis in the history of computing. It is postulated that the architecture and method utilized by the AlphaGo program provide an engineering solution for tackling issues in complexity and intelligence. Specifically, the AlphaGo Thesis implies that any effective procedure for hard decision problems such as NP-hard can be implemented with AlphaGo-like approach. Deep rule-based networks are proposed in attempt to establish an understandable structure for deep neural networks in deep learning. The success of AlphaGo and corresponding thesis ensure the technical soundness of the parallel intelligence approach for intelligent control and management of complex systems and knowledge automation. © 2014 Chinese Association of Automation.

关键词： Religious buildings

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Dynamics over signed networks

arXiv

引用

arXiv 2017年

作者： Shi, Guodong Altafini, Claudio Baras, John S. Australian Center for Field Robotics School of Aerospace Mechanical and Mechatronic Engineering University of Sydney NSW Australia Division of Automatic Control Department of Electrical Engineering Linköping University LinköpingSE-58183 Sweden Institute for Systems Research Department of Electrical and Computer Engineering University of Maryland College ParkMD20742 United States

A signed network is a network with each link associated with a positive or negative sign. Models for nodes interacting over such signed networks, where two different types of interactions take place along the positive and negative links, respectively, arise from various biological, social, political, and economic systems. As modifications to the conventional DeGroot dynamics for positive links, two basic types of negative interactions along negative links, namely the opposing rule and the repelling rule, have been proposed and studied in the literature. This paper reviews a few fundamental convergence results for such dynamics over deterministic or random signed networks under a unified algebraic-graphical method. We show that a systematic tool of studying node state evolution over signed networks can be obtained utilizing generalized Perron-Frobenius theory, graph theory, and elementary algebraic recursions. Copyright © 2017, The Authors. All rights reserved.

关键词： Algebra

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Solving almost all systems of random quadratic equations

arXiv

引用

arXiv 2017年

作者： Wang, Gang Giannakis, Georgios B. Saad, Yousef Chen, Jie Digital Technology Center Department of Electrical and Computer Engineering University of Minnesota MinneapolisMN55455 United States State Key Lab of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China Department of Computer Science and Engineering University of Minnesota MinneapolisMN55455 United States

This paper deals with finding an n-dimensional solution x to a system of quadratic equations of the form yi = jhai;xij2 for 1 ≤ i ≤ m, which is also known as phase retrieval and is NP-hard in general. We put forth a novel procedure for minimizing the amplitude-based least-squares empirical loss, that starts with a weighted maximal correlation initialization obtainable with a few power or Lanczos iterations, followed by successive refinements based upon a sequence of iteratively reweighted (generalized) gradient iterations. The two (both the initialization and gradient flow) stages distinguish themselves from prior contributions by the inclusion of a fresh (re)weighting regularization technique. The overall algorithm is conceptually simple, numerically scalable, and easy-to-implement. For certain random measurement models, the novel procedure is shown capable of finding the true solution x in time proportional to reading the data f(ai;yi)g1≤i≤m. This holds with high probability and without extra assumption on the signal x to be recovered, provided that the number m of equations is some constant c > 0 times the number n of unknowns in the signal vector, namely, m > cn. Empirically, the upshots of this contribution are: I) (almost) 100% perfect signal recovery in the high-dimensional (say e.g., n ≥2;000) regime given only an information-theoretic limit number of noiseless equations, namely, m = 2n - 1 in the real-valued Gaussian case;and, ii) (nearly) optimal statistical accuracy in the presence of additive noise of bounded support. Finally, substantial numerical tests using both synthetic data and real images corroborate markedly improved signal recovery performance and computational efficiency of our novel procedure relative to state-of-the-art approaches. Copyright © 2017, The Authors. All rights reserved.

关键词： Computational efficiency

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Compressive phase retrieval via reweighted amplitude flow

arXiv

引用

arXiv 2017年

作者： Zhang, Liang Wang, Gang Giannakis, Georgios B. Chen, Jie Digital Technology Center Department of Electrical and Computer Engineering University of Minnesota MinneapolisMN55455 United States State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China School of Automation State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China

The problem of reconstructing a sparse signal vector from magnitude-only measurements (a.k.a., compressive phase retrieval), emerges naturally in diverse applications, but it is NP-hard in general. Building on recent advances in nonconvex optimization, this paper puts forth a new algorithm that is termed compressive reweighted amplitude flow and abbreviated as CRAF, for compressive phase retrieval. Specifically, CRAF operates in two stages. The first stage seeks a sparse initial guess via a new spectral procedure. In the second stage, CRAF implements a few hard thresholding based iterations using reweighted gradients. When there are sufficient measurements, CRAF provably recovers the underlying signal vector exactly with high probability under suitable conditions. Moreover, its sample complexity coincides with that of the state-of-the-art procedures. Finally, substantial simulated tests showcase remarkable performance of the new spectral initialization, as well as improved exact recovery relative to competing alternatives. Copyright © 2017, The Authors. All rights reserved.

关键词： Iterative methods

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Formal framework and models for validation and verification of software-intensive aerospace systems

Formal framework and models for validation and verification ...

引用

AIAA Information systems-Infotech At Aerospace Conference, 2017

作者： Guarro, Sergio B. Yau, Michael K. Ozguner, Umit Aldemir, Tunc Kurt, Arda Hejase, Mohammad Knudson, Matt D. ASCA Inc. 1720 S. Catalina Avenue Suite 220 Redondo BeachCA90277 United States Department of Electrical and Computer Engineering Ohio State University 2015 Neil Ave ColumbusOH43210 United States Mechanical and Aerospace Engineering Department Ohio State University 201 W 19th Ave. ColumbusOH43210 United States NASA Ames Research Center Intelligent Systems Division Moffett Field Mail Stop 269-2 CA94035 United States

ISBN: (数字)9781624104497

ISBN: (纸本)9781624104497

Model-based control systems (MBCSs) and adaptive control systems (ACSs) represent an emerging class of software-intensive space and aeronautical control applications that bring tangible benefits to design processes and developments, but also challenges to traditional validation and verification (V&V) methods. This paper presents the results produced in the first two years of a three-year NASA project seeking the development of a comprehensive framework for the V&V of MBCSs and ACSs. The framework under development represents a comprehensive V&V methodology that utilizes Dynamic Flowgraph Methodology (DFM) and Markov-CCMT (Cell to Cell Mapping Technique) logic-dynamic model constructs, and associated time-dependent, deductive-inductive multi-valued logic analysis processes. This V&V framework produces formal evidence supporting the generation and documentation of an assurance case for a model-based control system, for the ultimate objective of demonstrating its compliance with design and safety requirements, and applicable software certification standards. © 2017, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Adaptive control systems

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