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11th International Conference on Bio-inspired Computing – Theories and Applications, BIC-TA 2016

作者： Fu, Qinhong Zhou, Kang Qi, Huaqing Wu, Tingfang School of Math and Computer Wuhan Polytechnic University WuhanHubei430023 China Department of Economics and Management Wuhan Polytechnic University WuhanHubei430023 China Key Laboratory of Image Information Processing and Intelligent Control School of Automation Huazhong University of Science and Technology WuhanHubei430074 China

ISBN: (纸本)9789811036132

The classical ant colony algorithm for vehicle routing problem with time windows (VRPTW) has problems of low efficiency, slow convergence and prematurity. And the discrete ant colony optimization (DACO) is proposed for these problem. It adopts the one-dimensional discrete coding that can make the data structure simpler and bring in faster convergence speed. In addition, self-convergence mode is used to calculate the optimal vehicle number rather than setting the optimal vehicle number at the beginning, which makes the algorithm more flexible and accelerates the convergence speed effectively. The time window and vehicle load are not considered in the optimization process, when ants complete the whole process and then the path is explained, this move not only expands the ant search scope but also improves the efficiency of the algorithm. The above highlights make the most of the selfadaptation and self-regulating mechanism, which effectively reduces the probability of the local optimal solution at the same time. Experimental results for Solomon benchmark test problems indicate that DACO outperforms both in reducing time and space complexity in the premise of not affecting the accuracy. Thus proves DACO is effective and feasible in solving the VRPTW. © Springer Nature Singapore Pte Ltd. 2016.

关键词： Ant colony optimization

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Author Correction: Why rankings of biomedical image analysis competitions should be interpreted with care

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Nature communications 2019年第1期10卷 588页

作者： Lena Maier-Hein Matthias Eisenmann Annika Reinke Sinan Onogur Marko Stankovic Patrick Scholz Tal Arbel Hrvoje Bogunovic Andrew P Bradley Aaron Carass Carolin Feldmann Alejandro F Frangi Peter M Full Bram van Ginneken Allan Hanbury Katrin Honauer Michal Kozubek Bennett A Landman Keno März Oskar Maier Klaus Maier-Hein Bjoern H Menze Henning Müller Peter F Neher Wiro Niessen Nasir Rajpoot Gregory C Sharp Korsuk Sirinukunwattana Stefanie Speidel Christian Stock Danail Stoyanov Abdel Aziz Taha Fons van der Sommen Ching-Wei Wang Marc-André Weber Guoyan Zheng Pierre Jannin Annette Kopp-Schneider Division of Computer Assisted Medical Interventions (CAMI) German Cancer Research Center (DKFZ) 69120 Heidelberg Germany. l.maier-hein@dkfz.de. Division of Computer Assisted Medical Interventions (CAMI) German Cancer Research Center (DKFZ) 69120 Heidelberg Germany. Centre for Intelligent Machines McGill University Montreal QC H3A0G4 Canada. Christian Doppler Laboratory for Ophthalmic Image Analysis Department of Ophthalmology Medical University Vienna 1090 Vienna Austria. Science and Engineering Faculty Queensland University of Technology Brisbane QLD 4001 Australia. Department of Electrical and Computer Engineering Department of Computer Science Johns Hopkins University Baltimore MD 21218 USA. CISTIB - Center for Computational Imaging & Simulation Technologies in Biomedicine The University of Leeds Leeds Yorkshire LS2 9JT UK. Department of Radiology and Nuclear Medicine Medical Image Analysis Radboud University Center 6525 GA Nijmegen The Netherlands. Institute of Information Systems Engineering TU Wien 1040 Vienna Austria. Complexity Science Hub Vienna 1080 Vienna Austria. Heidelberg Collaboratory for Image Processing (HCI Heidelberg University 69120 Heidelberg Germany. Centre for Biomedical Image Analysis Masaryk University 60200 Brno Czech Republic. Electrical Engineering Vanderbilt University Nashville TN 37235-1679 USA. Institute of Medical Informatics Universität zu Lübeck 23562 Lübeck Germany. Division of Medical Image Computing (MIC) German Cancer Research Center (DKFZ) 69120 Heidelberg Germany. Institute for Advanced Studies Department of Informatics Technical University of Munich 80333 Munich Germany. Information System Institute HES-SO Sierre 3960 Switzerland. Departments of Radiology Nuclear Medicine and Medical Informatics Erasmus MC 3015 GD Rotterdam The Netherlands. Department of Computer Science University of Warwick Coventry CV4 7AL UK. Department of Radiation Oncology Massachusetts General Hospital Boston MA

In the original version of this Article the values in the rightmost column of Table 1 were inadvertently shifted relative to the other columns. This has now been corrected in the PDF and HTML versions of the Article.

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Towards Robust Ego-Centric Hand Gesture Analysis for Robot Control

Towards Robust Ego-Centric Hand Gesture Analysis for Robot C...

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2016 IEEE International Conference on Signal and image processing

作者： Hongyong Song Weijiang Feng Naiyang Guan Xuhui Huang Zhigang Luo Institute of Software College of Computer National University of Defense Technology Department of Computer Science and Technology College of Computer National University of Defense Technology Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology

Wearable device with an ego-centric camera would be the next generation device for human-computer interaction such as robot *** gesture is a natural way of egocentric human-computer *** this paper, we present an ego-centric multi-stage hand gesture analysis pipeline for robot control which works robustly in the unconstrained environment with varying *** particular, we first propose an adaptive color and contour based hand segmentation method to segment hand region from the egocentric *** then propose a convex U-shaped curve detection algorithm to precisely detect positions of *** parallelly, we utilize the convolutional neural networks to recognize hand *** on these techniques, we combine most information of hand to control the robot and develop a hand gesture analysis system on an i Phone and a robot arm platform to validate its *** result demonstrates that our method works perfectly on controlling the robot arm by hand gesture in real time.

关键词： ego-centric vision hand detection and segmentation fingertips detection hand gesture recognition robot control human-computer interaction

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Cyber-physical System Security for Networked Industrial Processes

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International Journal of Automation and computing 2015年第6期12卷 567-578页

作者： Shuang Huang Chun-Jie Zhou Shuang-Hua Yang Yuan-Qing Qin School of Automation Huazhong University of Science and Technology Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Department of Computer Science Loughborough University

Cyber-physical systems(CPSs) are integrations of networks, computation and physical processes, where embedded computing devices continually sense, monitor, and control the physical processes through networks. Networked industrial processes combining internet, real-time computer control systems and industrial processes together are typical CPSs. With the increasingly frequent cyber-attack, security issues have gradually become key problems for CPSs. In this paper, a cyber-physical system security protection approach for networked industrial processes, i.e., industrial CPSs, is proposed. In this approach, attacks are handled layer by layer from general information technology(IT) security protection, to active protection, then to intrusion tolerance and physical security protection. The intrusion tolerance implemented in real-time control systems is the most critical layer because the real time control system directly affects the physical layer. This novel intrusion tolerance scheme with a closed loop defense framework takes into account the special requirements of industrial CPSs. To illustrate the effectiveness of the CPS security protection approach, a networked water level control system is described as a case study in the architecture analysis and design language(AADL) environment. Simulation results show that 3 types of injected attacks can be quickly defended by using the proposed protection approach.

关键词： Critical infrastructures cyber-physical systems(CP

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A multi-objective optimization algorithm based on tissue P system for VRPTW 11th

A multi-objective optimization algorithm based on tissue P s...

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11th International Conference on Bio-inspired Computing – Theories and Applications, BIC-TA 2016

作者： Dong, Wenbo Zhou, Kang Qi, Huaqing He, Cheng Zhang, Jun Song, Bosheng School of Math and Computer Wuhan Polytechnic University WuhanHubei430023 China Department of Economics and Management Wuhan Polytechnic University WuhanHubei430023 China Key Laboratory of Image Information Processing and Intelligent Control Huazhong University of Science and Technology WuhanHubei430074 China School of Automation Huazhong University of Science and Technology WuhanHubei430074 China

ISBN: (纸本)9789811036132

Vehicle routing problem with time windows has an important practical significance, but it is NP-Hard problem. In order to solve the problem, an optimization algorithm based on P system is proposed. The encoding of glowworm’s location is considered as evolutionary object and discrete glowworm evolution mechanism and variable neighborhood evolution mechanism are used as sub-algorithms. In this paper, the motion equations and related motion rules of glowworm algorithm are improved to optimize the performance of the algorithm. Meanwhile, in order to enlarge the search area of solution space and improve the precision, the variable neighborhood evolution mechanism is redesigned. Cell communication rules are used to exchange information between cells. Moreover, this paper introduced the concept of Pareto dominance to evaluate the advantages and disadvantages of the object, as a result, this method returns not a single non-dominated solution but a set of no-dominated solutions. At last, by solving the different Solomon numerical examples and simulation results show that the algorithm is easier to jump out of local optimal both achieves very good results in the number of vehicles and distance cost, besides, generates a lot of new solutions which are different from the database. This algorithm has the features of faster convergence rate and accurate precision, and it is competitive with other heuristic or metaheuristic algorithms in the literature. © Springer Nature Singapore Pte Ltd. 2016.

关键词： Multiobjective optimization

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Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge

arXiv

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arXiv 2018年

作者： Bakas, Spyridon Reyes, Mauricio Jakab, Andras Bauer, Stefan Rempfler, Markus Crimi, Alessandro Shinohara, Russell Takeshi Berger, Christoph Ha, Sung Min Rozycki, Martin Prastawa, Marcel Alberts, Esther Lipkova, Jana Freymann, John Kirby, Justin Bilello, Michel Fathallah-Shaykh, Hassan M. Wiest, Roland Kirschke, Jan Wiestler, Benedikt Colen, Rivka Kotrotsou, Aikaterini Lamontagne, Pamela Marcus, Daniel Milchenko, Mikhail Nazeri, Arash Weber, Marc-Andr Mahajan, Abhishek Baid, Ujjwal Gerstner, Elizabeth Kwon, Dongjin Acharya, Gagan Agarwal, Manu Alam, Mahbubul Albiol, Alberto Albiol, Antonio Albiol, Francisco J. Alex, Varghese Allinson, Nigel Amorim, Pedro H.A. Amrutkar, Abhijit Anand, Ganesh Andermatt, Simon Arbel, Tal Arbelaez, Pablo Avery, Aaron Azmat, Muneeza Pranjal, B. Bai, Wenjia Banerjee, Subhashis Barth, Bill Batchelder, Thomas Batmanghelich, Kayhan Battistella, Enzo Beers, Andrew Belyaev, Mikhail Bendszus, Martin Benson, Eze Bernal, Jose Bharath, Halandur Nagaraja Biros, George Bisdas, Sotirios Brown, James Cabezas, Mariano Cao, Shilei Cardoso, Jorge M. Carver, Eric N. Casamitjana, Adri Castillo, Laura Silvana Cat, Marcel Cattin, Philippe Cérigues, Albert Chagas, Vinicius S. Chandra, Siddhartha Chang, Yi-Ju Chang, Shiyu Chang, Ken Chazalon, Joseph Chen, Shengcong Chen, Wei Chen, Jefferson W. Chen, Zhaolin Cheng, Kun Choudhury, Ahana Roy Chylla, Roger Clrigues, Albert Colleman, Steven Colmeiro, Ramiro German Rodriguez Combalia, Marc Costa, Anthony Cui, Xiaomeng Dai, Zhenzhen Dai, Lutao Daza, Laura Alexandra Deutsch, Eric Ding, Changxing Dong, Chao Dong, Shidu Dudzik, Wojciech Eaton-Rosen, Zach Egan, Gary Escudero, Guilherme Estienne, Tho Everson, Richard Fabrizio, Jonathan Fan, Yong Fang, Longwei Feng, Xue Ferrante, Enzo Fidon, Lucas Fischer, Martin French, Andrew P. Fridman, Naomi Fu, Huan Fuentes, David Gao, Yaozong Gates, Evan Gering, David Gholami, Amir Gierke, Willi Glocker, Ben Gong, Mingming Gonzlez-Vill, Sandra Grosges, T. Guan, Yuanfang Guo, Sheng Gupta, Sudeep Han, Woo-Sup Han, Il Song Harmuth, Ko Center for Biomedical Image Computing and Analytics University of Pennsylvania PhiladelphiaPA United States Department of Radiology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Institute for Surgical Technology and Biomechanics University of Bern Bern Switzerland Center for MR-Research University Children's Hospital Zurich Zurich Switzerland Support Centre for Advanced Neuroimaging Inselspital Institute for Diagnostic and Interventional Neuroradiology Bern University Hospital Bern Switzerland University Hospital of Zurich Zurich Switzerland Center for Clinical Epidemiology and Biostatistics University of Pennsylvania Philadelphia United States Image-Based Biomedical Modeling Group Technical University of Munich Munich Germany Icahn School of Medicine Mount Sinai Health System New YorkNY United States Leidos Biomedical Research Inc. Frederick National Laboratory for Cancer Research FrederickMD21701 United States Cancer Imaging Program National Cancer Institute National Institutes of Health BethesdaMD20814 United States Department of Neurology University of Alabama at Birmingham BirminghamAL United States Department of Diagnostic Radiology University of Texas MD Anderson Cancer Center HoustonTX United States Department of Psychology Washington University St. LouisMO United States Neuroimaging Informatics and Analysis Center Washington University St. LouisMO United States Department of Radiology Washington University St. LouisMO United States Institute of Diagnostic and Interventional Radiology Pediatric Radiology and Neuroradiology University Medical Center Rostock Ernst-Heydemann-Str. 6 Rostock18057 Germany Tata Memorial Centre Homi Bhabha National Institute Mumbai India Shri Guru Gobind Singhji Institute of Engineering and Technology Nanded India NVIDIA Santa Clara

Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrotic core, active and non-enhancing core. This intrinsic heterogeneity is also portrayed in their radio-phenotype, as their sub-regions are depicted by varying intensity profiles disseminated across multi-parametric magnetic resonance imaging (mpMRI) scans, reflecting varying biological properties. Their heterogeneous shape, extent, and location are some of the factors that make these tumors difficult to resect, and in some cases inoperable. The amount of resected tumor is a factor also considered in longitudinal scans, when evaluating the apparent tumor for potential diagnosis of progression. Furthermore, there is mounting evidence that accurate segmentation of the various tumor sub-regions can offer the basis for quantitative image analysis towards prediction of patient overall survival. This study assesses the state-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i.e., 2012-2018. Specifically, we focus on i) evaluating segmentations of the various glioma sub-regions in pre-operative mpMRI scans, ii) assessing potential tumor progression by virtue of longitudinal growth of tumor sub-regions, beyond use of the RECIST/RANO criteria, and iii) predicting the overall survival from pre-operative mpMRI scans of patients that underwent gross total resection. Finally, we investigate the challenge of identifying the best ML algorithms for each of these tasks, considering that apart from being diverse on each instance of the challenge, the multi-institutional mpMRI BraTS dataset has also been a continuously evolving/growing dataset. Copyright © 2018, The Authors. All rights reserved.

关键词： Tumors

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A Switching Approach to Designing Finite-Time Synchronization Controllers of Coupled Neural Networks

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IEEE Transactions on Neural Networks and Learning Systems 2016年第2期27卷 471-482页

作者： Liu, Xiaoyang Su, Housheng Chen, Michael Z. Q. School of Computer Science and Technology Jiangsu Normal University Xuzhou221116 China Image Processing and Intelligent Control Key Laboratory School of Automation Huazhong University of Science and Technology Wuhan430074 China Department of Mechanical Engineering University of Hong Kong Hong Kong Hong Kong

This paper is concerned with the finite-Time synchronization issue of nonlinear coupled neural networks by designing a new switching pinning controller. For the fixed network topology and control strength, the newly d... 详细信息

关键词： Network topology

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Matrix flat splicing systems 11th

Matrix flat splicing systems

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11th International Conference on Bio-inspired Computing – Theories and Applications, BIC-TA 2016

作者： Ceterchi, Rodica Pan, Linqiang Song, Bosheng Subramanian, K.G. Faculty of Mathematics and Computer Science University of Bucharest 14 Academiei Street Bucharest010014 Romania School of Electric and Information Engineering Zhengzhou University of Light Industry ZhengzhouHenan450002 China Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China School of Automation Huazhong University of Science and Technology WuhanHubei430074 China Department of Mathematics Madras Christian College Chennai600059 India

ISBN: (纸本)9789811036101

In dealing with the problem of modelling DNA recombination, the operation of splicing on linear and circular strings of symbols was introduced. Inspired by splicing on circular strings, the operation of flat splicing on a pair of strings (u, v) was considered. This operation involves "cutting" u at a specified position and "inserting" v into it, with v having a pre-specified prefix as well as suffix defined by a flat splicing rule. In this work, we consider a well-known technique in formal language theory, known as "matrix of rules", and introduce matrix of flat splicing rules and thus define matrix flat splicing system (MFSS). Some results on the language generative power of MFSS are provided. An application of MFSS in the generation of chain code pictures is also pointed out. © Springer Nature Singapore Pte Ltd. 2016.

关键词： Formal languages

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Suspicious face detection based on key frame recognition under surveillance video

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2016年 9712 LNCS卷 645-652页

作者： Zheng, Xiaohui Ning, Yi Chen, Xianjun Zhan, Yongsong Guangxi Colleges and Universities Key Laboratory of Intelligent Processing of Computer Image and Graphics Guilin University of Electronic Technology GuilinGuangxi541004 China Guangxi Experiment Center of Information Science Guilin University of Electronic Technology GuilinGuangxi541004 China Guangxi Colleges and Universities Key Laboratory of Cloud Computing and Complex Systems Guilin University of Electronic Technology GuilinGuangxi541004 China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology GuilinGuangxi541004 China

ISBN: (纸本)9783319409993

Surveillance video is characterized by large amount of data and redundancy, which makes the suspicious face detection to be a problem. To solve the problem above we proposed suspicious face detection based on key frame. Surveillance video has the type of fixed background, so this paper used the frame difference method with low computational complexity and small computation to extract the key frame. We proposed a new method combined DPM with skin color detection to detect the suspicious face in the key frames. To solve the speed bottleneck of the traditional DPM, we proposed to use the fast HOG LUT feature extraction and the near optimal cost sensitive decision making improving the traditional method. Meanwhile we used YCrCb + otsu skin color segmentation. Since the otsu is easily affected by the illumination, we proposed an improved skin color detection. Experiment results show that the proposed algorithms are robust and accurate for real-time. © Springer International Publishing Switzerland 2016.

关键词： Face recognition

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An improved reference point sampling method on Pareto optimal front

An improved reference point sampling method on Pareto optima...

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Congress on Evolutionary Computation

作者： Cheng He Linqiang Pan Hang Xu Ye Tian Xingyi Zhang Laboratory of Image Information Processing and Intelligent Control Huazhong University of Science and Technology Wuhan Hubei China Huazhong University of Science and Technology Wuhan Hubei CN Department of Computer Science Xiamen University Xiamen Fujian China Key Lab of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei Anhui China

ISBN: (纸本)9781509006243

In this paper, we propose a sampling approach of reference points used for performance metrics of multi-objective evolutionary algorithms. Traditional reference point sampling methods, such as the Das and Dennis method, usually sample the reference points via a set of uniformly distributed weight vectors generated on an ideal hyper-plane in objective space, which however often ignore the geometric shape of a specific Pareto front. Therefore, we propose a novel reference point sampling approach by taking the specific shape of the Pareto optimal front to be tackled into account for measuring the performance of multi-objective evolutionary algorithms. The performance of the proposed reference point sampling method against the other two state-of-the-art sampling methods is tested on six test instances in various conditions, which clearly demonstrate the effectiveness and superiority of the proposed sampling method.

关键词： Sampling methods Shape Convergence Evolutionary computation Optimization Euclidean distance

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