检索结果-内蒙古大学图书馆

10th International Conference on Computer Vision Theory and Applications, VISAPP 2015

作者： Abdul-Kreem, Luma Issa Neumann, Heiko Inst. for Neural Information Processing Ulm University Ulm Germany Control and Systems Engineering Dept. University of Technology Baghdad Iraq

ISBN: (纸本)9789897580918

In this paper, we propose a new bio-inspired approach for motion estimation using a Dynamic Vision Sensor (DVS) (Lichtsteiner et al., 2008), where an event-based-temporal window accumulation is introduced. This format accumulates the activity of the pixels over a short time, i.e. several fis. The optic flow is estimated by a new neural model mechanism which is inspired by the motion pathway of the visual system and is consistent with the vision sensor functionality, where new temporal filters are proposed. Since the DVS already generates temporal derivatives of the input signal, we thus suggest a smoothing temporal filter instead of biphasic temporal filters that introduced by (Adelson and Bergen, 1985). Our model extracts motion information via a spatiotemporal energy mechanism which is oriented in the space-time domain and tuned in spatial frequency. To achieve balanced activities of individual cells against the neighborhood activities, a normalization process is carried out. We tested our model using different kinds of stimuli that were moved via translatory and rotatory motions. The results highlight an accurate flow estimation compared with synthetic ground truth. In order to show the robustness of our model, we examined the model by probing it with synthetically generated ground truth stimuli and realistic complex motions, e.g. biological motions and a bouncing ball, with satisfactory results.

关键词： Motion estimation

来源：评论

学校读者我要写书评

暂无评论

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

arXiv

引用

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

来源：评论

学校读者我要写书评

暂无评论

An Iterative Procedure for Multidimensional Realization By LFT Techniques

引用

IFAC Proceedings Volumes 2012年第13期45卷 723-727页

作者： Huijin Fan Li Xu Kose Uemura Shinya Matsushita Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Dept. Control Science & Engineering Huazhong University of Science and Technology P. R. China Dept. of Electronic and Information Systems Akita Prefectural University Akita Japan

In this paper, by utilizing Linear Fractional Transformation (LFT) techniques, an iterative realization procedure resulting in multidimensional ( n -D) Roesser state-space model is proposed. The philosophy employed here is to achieve an overall n -D realization by realizing relatively lower-dimensional systems with respect to (w.r.t.) less-number of variables iteratively. Symbolic examples are presented to illustrate the basic idea as well as the effectiveness of the proposed procedure.

关键词：

来源：评论

学校读者我要写书评

暂无评论

control SYSTEM DESIGN CONSIDERING A TRADEOFF BETWEEN EVALUATED UNCERTAINTY RANGES AND control PERFORMANCE

引用

Asian Journal of control 2008年第1期1卷

作者： Y. Wakasa Y. Yamamoto Dept. of Applied Analysis and Complex Dynamical Systems Graduate School of Informatics Kyoto University Kyoto Japan. Yuji Wakasa was born in Okayama Japan in 1968. He received the B.S. and M.S. degrees in engineering from Kyoto university Japan in 1992 and 1994 respectively. From 1994 to 1998 he was a Research Associate in the Department of Information Technology Okayama University. Since April 1998 he has been a Research Associate in the Graduate School of Informatics Kyoto University. His current research interests include robust control and control system design via mathematical programming. Yutaka Yamamoto received his B.S. and M.S. degrees in engineering from Kyoto University Kyoto Japan in 1972 and 1974 respectively and the M.S. and Ph.D. degree in mathematics from the University of Florida in 1976 and 1978 respectively. From 1978 to 1987 he was with Department of Applied Mathematics and Physics Kyoto University and from 1987 to 1997 with Department of Applied System Science. Since 1998 he is a professor at the current position. His current research interests include realization and robust control of distributed parameter systems learning control sampled-data systems and digital signal processing. Dr. Yamamoto is a receipient of the Sawaragi memorial paper award (1985) the Outstanding Paper Award of SICE (1987) Best Author Award of SICE (1990) the George Axelby Outstanding Paper Award of IEEE CSS in 1996 Takeda Paper Prize of SICE in 1997. He is a Fellow of IEEE. He was an associate editor of Automatica. He is currently an associate editor of IEEE Transactions on Automatic Control Systems and Control Letters and Mathematics of Control Signals and Systems. He is a member of the IEEE the Society of Instrument and Control Engineers (SICE) and the Institute of Systems Control and Information Engineers.

This paper presents a design method of control systems such that a designer can flexibly take account of tradeoffs between evaluated uncertainty ranges and the level of control performance. The problem is reduced to a BMI problem and approximately solved by LMIs. The convergence of the proposed approximation is proved in a modified sense. A numerical example shows the effectiveness of the proposed method in comparison with the standard robust control.

关键词： control system design LMI BMI tradeoff curves

来源：评论

学校读者我要写书评

暂无评论

LANDING AN UNMANNED AIR VEHICLE: VISION BASED MOTION ESTIMATION AND NONLINEAR control

引用

Asian Journal of control 2008年第3期1卷

作者： Omid Shakernia Yi Ma T. John Koo Shankar Sastry Dept. of Electrical Engineering & Computer Science University of California at Berkeley Berkeley CA94720-1774 U.S.A. Tak-Kuen John Koo received the B.Eng. degree in 1992 in Electronic Engineering and the M.Phil. in 1994 in Information Engineering both from the Chinese University of Hong Kong. From 1994 to 1995 he was a graduate student in Signal and Image Processing Institute at the University of Southern California. He is currently a Ph.D. Candidate in Electrical Engineering and Computer Sciences at the University of California at Berkeley. His research interests include nonlinear control theory hybrid systems inertial navigation systems with applications to unmanned aerial vehicles. He received the Distinguished M.Phil. Thesis Award of the Faculty of Engineering The Chinese University of Hong Kong in 1994. He was a consultant of SRI International in 1998. Currently he is the team leader of the Berkeley AeRobot Team and a delegate of The Graduate Assembly University of California at Berkeley. He is a student member of IEEE and SIAM. S. Shankar Sastry received his Ph.D. degree in 1981 from the University of California Berkeley. He was on the faculty of MIT from 1980-82 and Harvard University as a Gordon McKay professor in 1994. He is currently a Professor of Electrical Engineering and Computer Sciences and Bioengineering and Director of the Electronics Research Laboratory at Berkeley. He has held visiting appointments at the Australian National University Canberra the University of Rome Scuola Normale and University of Pisa the CNRS laboratory LAAS in Toulouse (poste rouge) and as a Vinton Hayes Visiting fellow at the Center for Intelligent Control Systems at MIT. His areas of research are nonlinear and adaptive control robotic telesurgery control of hybrid systems and biological motor control. He is a coauthor (with M. Bodson) of “Adaptive Control: Stability Convergence and Robustness Prentice Hall 1989.” and (with R. Murray and Z. Li) of “A Mathematical Introduction to Robotic Manipulati

In this paper, we use computer vision as a feedback sensor in a control loop for landing an unmanned air vehicle (UAV) on a landing pad. The vision problem we address here is then a special case of the classic ego-motion estimation problem since all feature points lie on a planar surface (the landing pad). We study together the discrete and differential versions of the ego-motion estimation, in order to obtain both position and velocity of the UAV relative to the landing pad. After briefly reviewing existing algorithm for the discrete case, we present, in a unified geometric framework, a new estimation scheme for solving the differential case. We further show how the obtained algorithms enable the vision sensor to be placed in the feedback loop as a state observer for landing control. These algorithms are linear, numerically robust, and computationally inexpensive hence suitable for real-time implementation. We present a thorough performance evaluation of the motion estimation algorithms under varying levels of image measurement noise, altitudes of the camera above the landing pad, and different camera motions relative to the landing pad. A landing controller is then designed for a full dynamic model of the UAV. Using geometric nonlinear control theory, the dynamics of the UAV are decoupled into an inner system and outer system. The proposed control scheme is then based on the differential flatness of the outer system. For the overall closed-loop system, conditions are provided under which exponential stability can be guaranteed. In the closed-loop system, the controller is tightly coupled with the vision based state estimation and the only auxiliary sensor are accelerometers for measuring acceleration of the UAV. Finally, we show through simulation results that the designed vision-in-the-loop controller generates stable landing maneuvers even for large levels of image measurement noise. Experiments on a real UAV will be presented in future work.

关键词： Motion estimation computer vision based control unmanned air vehicle differential flatness

来源：评论

学校读者我要写书评

暂无评论

A novel approach to automatic music composing: Using genetic algorithm

A novel approach to automatic music composing: Using genetic...

引用

International Computer Music Conference, ICMC 2006

作者： Zad, Damon Daylamani Araabi, Babak N. Lucas, Caru Department of Information Systems and Computing Brunel University United Kingdom Dept. of Electrical and Computer Engineering Control and Intelligent Processing Center of Excellence University of Tehran Iran

Artificial music composition is one of the ever rising problems of computer science. Genetic Algorithm has been one of the most useful means in our hands to solve optimization problems. By use of precise assumptions and adequate fitness function it is possible to change the music composing into an optimization problem. This paper proposes a new genetic algorithm for composing music. Considering entropy of the notes distribution as a factor of fitness function and developing mutation and crossover functions based on harmonic rules and trying to keep the melodies intact during these processes would result in a musical piece pleasant to human ears and interesting for human mind. This algorithm does not have the constraints of the previous algorithms. Restraining mutation and crossover functions with a goal of producing melodies based on acceptable melodies composed by humans, this algorithm is not bound to any genre, instrument or melody. The experimental results of this approach show that it is near to the human composing and the results produced from it are more acceptable than the ones produced by its predecessors.

关键词： Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

On the Estimation of Optimal Weights for Instrumental Variable System Identification Methods

引用

IFAC Proceedings Volumes 2000年第15期33卷 923-928页

作者： Petre Stoica Magnus Jansson Dept. of Systems and Control Information Technology Uppsala University Uppsala Sweden Dept. of Signals Sensors and Systems Signal Processing Royal Inst. of Technology (KTH) Stockholm Sweden

It is well known that the accuracy of instrumental variable (IV) methods for parameter estimation can be significantly improved by weighting the estimating equations. However, the optimal weight typically depends on unknown parameters and needs to be estimated before it can be used in the IV estimator. In many parameter estimation problems the optimal weighting matrix is equal to the DC power of a certain vector process. It is known to be a difficult task to consistently estimate power in a nonparametric manner at any frequency (e.g., the periodogram cannot achieve this). However, for the case considered in this paper we show that there exists a natural nonparametric consistent estimator of the DC power matrix or, equivalently, the optimal weighting matrix. This result is expected to increase the interest in using optimally weighted parameter estimation methods of instrumental variable or related type.

关键词： Identification estimation theory parameter estimation weighting functions non-parametric identification spectral analysis consistency

来源：评论

学校读者我要写书评

暂无评论

COMMERCIAL APPLICATIONS OF ADVANCED MARINE VEHICLES FOR EXPRESS SHIPPING

引用

NAVAL ENGINEERS JOURNAL 1983年第3期95卷 283-300页

作者： LUEDEKE, G FARNHAM, RB JR. George Luedeke Jr.: received his BS degree in Mechanical Engineering from Massachusetts Institute of Technology and his MS degree in Product Design from Illinois Institute of Technology. Early in his career Mr. Luedeke joined General Motors Corporation as a designer responsible for development of people mover and rail rapid transit systems. From 1964 to 1974 he was with Hughes Aircraft Company. At Hughes he performed analyses and developed designs for a wide variety of program and proposal efforts such as: High Speed Ground Transportation (DOT) Task Force Command Center (NAVY) Panama Canal Marine Traffic Control Center (Panama Canal Co.) Royal Iranian Navy Command Center (Iran) Tactical Information Processing and Interpretation Center (Air Force) and WALLEYE CONDOR and PHOENIX Missile Systems (NAVY). He also had marketing development responsibilities related to the diversification of Hughes resources in civil business areas such as: Automatic train control (WMATA BARTD SCRTD) water/sewage treatment plant automation (Santa Clara County) Aqueduct Control (SWR) Hydrometeorological data collection (BPA WMO) and Salton Sea basin systems analysis (Dept. of the Interior). He was responsible for combat system integration for the Hughes 2000T Surface Effect Ship (SES) proposal. He also conducted detailed studies concerning ship flexure for the Improved Point Defense Target Acquisition System Program and for the definition of operational High Energy Laser weapon installations on a series of conventional monohulls (DLG DD and CVN). Since 1974 Mr. Luedeke has been employed at RMI Inc. (formerly Rohr Marine Inc.). During this time he has held several positions. His responsibilities have included directing a number of studies on advanced SES concepts managing activities defining mission/cost effectiveness of military and commercial SES's including defining the operational benefits and enhanced survivability characteristics of cargo SES's for high speed military sealiftfor NA TO and Southeast Asia

This paper will present the results of a marketing, engineering, and economic analysis of advanced marine vehicles done by IMA Resources, Inc. and RMI, Inc., in support of a Maritime Administration project to study “Multimode Express Shipping”. The study was conducted in 1981 and examined the economic benefits of using advanced marine vehicles as express cargo vessels in domestic and international service. Commodity characteristics, desirable express carrier rates, and potential high payoff service and route alternatives were identified. Advanced marine vehicles were surveyed and sized to meet desirable deadweight and block speed objectives. The costs of operating these craft on a variety of trade routes were calculated using an advanced marine vehicle economic analysis program. Revenues, expenses, break-even, profit and loss, cash flow requirements, tax summary and economic indicators (i.e., cost/ton – mile, etc.) were projected over the expected life of the vehicles as was return on investment. Traffic density and market penetration considerations narrowed the field of choice to smaller sized advanced marine vehicle carriers (i.e., 50 and 250 ton deadweight) and to three international and five domestic routes.

关键词：

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：