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arXiv 2021年

作者： Reinke, Annika Tizabi, Minu D. Sudre, Carole H. Eisenmann, Matthias Rädsch, Tim Baumgartner, Michael Acion, Laura Antonelli, Michela Arbel, Tal Bakas, Spyridon Bankhead, Peter Benis, Arriel Blaschko, Matthew Buettner, Florian Cardoso, M. Jorge Chen, Jianxu Cheplygina, Veronika Christodoulou, Evangelia Cimini, Beth A. Collins, Gary S. Engelhardt, Sandy Farahani, Keyvan Ferrer, Luciana Galdran, Adrian van Ginneken, Bram Glocker, Ben Godau, Patrick Haase, Robert Hamprecht, Fred Hashimoto, Daniel A. Heckmann-Nötzel, Doreen Hirsch, Peter Hoffman, Michael M. Huisman, Merel Isensee, Fabian Jannin, Pierre Kahn, Charles E. Kainmueller, Dagmar Kainz, Bernhard Karargyris, Alexandros Karthikesalingam, Alan Kavur, A. Emre Kenngott, Hannes Kleesiek, Jens Kleppe, Andreas Koehler, Sven Kofler, Florian Kopp-Schneider, Annette Kooi, Thijs Kozubek, Michal Kreshuk, Anna Kurc, Tahsin Landman, Bennett A. Litjens, Geert Madani, Amin Maier-Hein, Klaus Martel, Anne L. Mattson, Peter Meijering, Erik Menze, Bjoern Moher, David Moons, Karel G.M. Müller, Henning Nichyporuk, Brennan Nickel, Felix Noyan, M. Alican Petersen, Jens Polat, Gorkem Rafelski, Susanne M. Rajpoot, Nasir Reyes, Mauricio Rieke, Nicola Riegler, Michael A. Rivaz, Hassan Saez-Rodriguez, Julio Sánchez, Clara I. Schroeter, Julien Saha, Anindo Selver, M. Alper Sharan, Lalith Shetty, Shravya Smeden, Maarten V.A.N. Stieltjes, Bram Summers, Ronald M. Taha, Abdel A. Tiulpin, Aleksei Tsaftaris, Sotirios A. Calster, Ben V.A.N. Varoquaux, Gaël Wiesenfarth, Manuel Yaniv, Ziv R. Jäger, Paul Maier-Hein, Lena Division of Intelligent Medical Systems and HI Helmholtz Imaging Heidelberg Germany Faculty of Mathematics and Computer Science Heidelberg University Heidelberg Germany Division of Intelligent Medical Systems Heidelberg Germany NCT Heidelberg DKFZ University Medical Center Heidelberg Germany MRC Unit for Lifelong Health and Ageing UCL Centre for Medical Image Computing Department of Computer Science University College London London United Kingdom School of Biomedical Engineering and Imaging Science King’s College London London United Kingdom Division of Medical Image Computing Heidelberg Germany Instituto de Cálculo CONICET – Universidad de Buenos Aires Buenos Aires Argentina Centre for Medical Image Computing University College London London United Kingdom McGill University Montréal Canada Division of Computational Pathology Dept of Pathology & Laboratory Medicine Indiana University School of Medicine IU Health Information and Translational Sciences Building Indianapolis United States University of Pennsylvania Richards Medical Research Laboratories FL7 PhiladelphiaPA United States Institute of Genetics and Cancer University of Edinburgh Edinburgh United Kingdom Department of Digital Medical Technologies Holon Institute of Technology Holon Israel European Federation for Medical Informatics Le Mont-sur-Lausanne Switzerland Center for Processing Speech and Images Department of Electrical Engineering KU Leuven Kasteelpark Arenberg 10 - box 2441 Leuven3001 Belgium Frankfurt/Mainz DKFZ UCT Frankfurt-Marburg Germany Heidelberg Germany Goethe University Frankfurt Department of Medicine Germany Goethe University Frankfurt Department of Informatics Germany Frankfurt Cancer Insititute Germany Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V. Dortmund Germany Department of Computer Science IT University of Copenhagen Copenhagen Denmark Imaging Platform Broad Institute of MIT and Harvard CambridgeMA United States Centre for St

While the importance of automatic image analysis is continuously increasing, recent meta-research revealed major flaws with respect to algorithm validation. Performance metrics are particularly key for meaningful, objective, and transparent performance assessment and validation of the used automatic algorithms, but relatively little attention has been given to the practical pitfalls when using specific metrics for a given image analysis task. These are typically related to (1) the disregard of inherent metric properties, such as the behaviour in the presence of class imbalance or small target structures, (2) the disregard of inherent data set properties, such as the non-independence of the test cases, and (3) the disregard of the actual biomedical domain interest that the metrics should reflect. This living dynamically document has the purpose to illustrate important limitations of performance metrics commonly applied in the field of image analysis. In this context, it focuses on biomedical image analysis problems that can be phrased as image-level classification, semantic segmentation, instance segmentation, or object detection task. The current version is based on a Delphi process on metrics conducted by an international consortium of image analysis experts from more than 60 institutions worldwide. © 2021, CC BY.

关键词： Medical imaging

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Supervised Online Hashing via Similarity Distribution Learning

arXiv

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arXiv 2019年

作者： Lin, Mingbao Ji, Rongrong Chen, Shen Zheng, Feng Sun, Xiaoshuai Zhang, Baochang Cao, Liujuan Guo, Guodong Huang, Feiyue Fujian Key Laboratory of Sensing and Computing for Smart City School of Information Science and Engineering Xiamen University China Peng Cheng Laboratory China Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China School of Automation Science and Electrical Engineering Beihang University China Baidu Research Institute of Deep Learning Co. Ltd China

Online hashing has attracted extensive research attention when facing streaming data. Most online hashing methods, learning binary codes based on pairwise similarities of training instances, fail to capture the semantic relationship, and suffer from a poor generalization in largescale applications due to large variations. In this paper, we propose to model the similarity distributions between the input data and the hashing codes, upon which a novel supervised online hashing method, dubbed as Similarity Distribution based Online Hashing (SDOH), is proposed, to keep the intrinsic semantic relationship in the produced Hamming space. Specifically, we first transform the discrete similarity matrix into a probability matrix via a Gaussianbased normalization to address the extremely imbalanced distribution issue. And then, we introduce a scaling Student t-distribution to solve the challenging initialization problem, and efficiently bridge the gap between the known and unknown distributions. Lastly, we align the two distributions via minimizing the Kullback-Leibler divergence (KL-diverence) with stochastic gradient descent (SGD), by which an intuitive similarity constraint is imposed to update hashing model on the new streaming data with a powerful generalizing ability to the past data. Extensive experiments on three widely-used benchmarks validate the superiority of the proposed SDOH over the state-of-the-art methods in the online retrieval task. Copyright © 2019, The Authors. All rights reserved.

关键词： Probability distributions

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Towards Orientation Learning and Adaptation in Cartesian Space

arXiv

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arXiv 2019年

作者： Huang, Yanlong Abu-Dakka, Fares J. Silvério, João Caldwell, Darwin G. School of Computing University of Leeds LeedsLS29JT United Kingdom Intelligent Robotics Group The Department of Electrical Engineering and Automation Aalto University Finland Idiap Research Institute MartignyCH-1920 Switzerland Department of Advanced Robotics Istituto Italiano di Tecnologia Via Morego 30 Genoa16163 Italy

As a promising branch of robotics, imitation learning emerges as an important way to transfer human skills to robots, where human demonstrations represented in Cartesian or joint spaces are utilized to estimate task/skill models that can be subsequently generalized to new situations. While learning Cartesian positions suffices for many applications, the end-effector orientation is required in many others. Despite recent advances in learning orientations from demonstrations, several crucial issues have not been adequately addressed yet. For instance, how can demonstrated orientations be adapted to pass through arbitrary desired points that comprise orientations and angular velocities? In this paper, we propose an approach that is capable of learning multiple orientation trajectories and adapting learned orientation skills to new situations (e.g., via-points and end-points), where both orientation and angular velocity are considered. Specifically, we introduce a kernelized treatment to alleviate explicit basis functions when learning orientations, which allows for learning orientation trajectories associated with high-dimensional inputs. In addition, we extend our approach to the learning of quaternions with angular acceleration or jerk constraints, which allows for generating smoother orientation profiles for robots. Several examples including experiments with real 7-DoF robot arms are provided to verify the effectiveness of our method. Copyright © 2019, The Authors. All rights reserved.

关键词： Angular velocity

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Spatial sparse subspace clustering for compressive spectral imaging

arXiv

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arXiv 2019年

作者： Zhu, Jianchen Zhang, Tong Zhao, Shengjie Hinojosa, Carlos Liu, Zengli Arce, Gonzalo R. Key Laboratory of Embedded System and Service Computing Ministry of Education School of Software Engineering Tongji University Shanghai201804 China School of Electronic and Information Engineering Tongji University Shanghai201804 China Department of System Engineering and Informatics Universidad Industrial de Santander Bucaramanga680002 Colombia Institute of information engineering and automation Computer Center Kunming University of Science and Technology Kunming650500 China Department of Electrical and Computer Engineering University of Delaware NewarkDE19716 United States

This paper aims at developing a clustering approach with spectral images directly from CASSI compressive measurements. The proposed clustering method first assumes that compressed measurements lie in the union of multiple low-dimensional subspaces. Therefore, sparse subspace clustering (SSC) is an unsupervised method that assigns compressed measurements to their respective subspaces. In addition, a 3D spatial regularizer is added into the SSC problem, thus taking full advantages of the spatial information contained in spectral images. The performance of the proposed spectral image clustering approach is improved by taking optimal CASSI measurements obtained when optimal coded apertures are used in CASSI system. Simulation with one real dataset illustrates the accuracy of the proposed spectral image clustering approach. Copyright © 2019, The Authors. All rights reserved.

关键词： Spectroscopy

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Output Group Consensus for Heterogeneous Linear Multi-Agent Systems Communicating over Switching Topology 36

Output Group Consensus for Heterogeneous Linear Multi-Agent ...

引用

第36届中国控制会议

作者： Jiahu Qin Qichao Ma Wei Xing Zheng Department of Automation University of Science and Technology of China School of Computing Engineering and MathematicsWestern Sydney University

ISBN: (纸本)9781538629185

In this paper,we aim to investigate the output group consensus problem for a switching network of heterogeneous linear systems such that outputs of the agents synchronize with each other in every *** the internal model principle perspective,a necessary condition is first derived in terms of the system *** this necessary condition,a dynamic controller is then designed to solve the output group consensus problem in two steps,namely consensus of reference generators and output tracking for each *** is obtained that if every possible underlying topology of each cluster contains a directed spanning tree,then group consensus for the reference generators can be realized with sufficiently strong intra-cluster coupling *** appropriate controller is then designed to force the output of each agent to track the output of the reference generators.A simulation example is given at last to validate our theoretical findings.

关键词： Output group consensus switching topology heterogeneous systems internal model principle

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Design and Implementation of RFID based Smart Shopping Booth

Design and Implementation of RFID based Smart Shopping Booth

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International Conference on Information Science and Control engineering (ICISCE)

作者： Ehtisham Lodhi Fenghua Zhu Zeeshan Lodhi Qasim Saleem Gang Xiong FeiYue Wang The State Key Laboratory for Management and Control of Complex Systems Chinese Academy of Sciences Beijing China Department of Electrical and Computer Engineering COMSATS University Islamabad Pakistan School of Automation Science and Electrical Engineering Beihang University Beijing China The Cloud Computing Center Chinese Academy of Sciences Dongguan China Beijing Engineering Research Center of Intelligent Systems and Technology Chinese Academy of Sciences Beijing China

ISBN: (数字)9781728157122

ISBN: (纸本)9781728157139

In this modern era, technology has advanced to such an extent to make our daily life more proficient and convenient. This paper presents the design and implementation of vending machine (VM) for students, which operates on radio frequency identification technology (RFID). Hence, it turns the VM into smart shopping booth (SSB). The SSB gives the access only through RFID card and vend different products according to the desire of student. The SSB is equipped with RFID reader and student identity card that holds the RFID tag. When the student identity card is scanned for verification and then after selecting the required products, will be dispensed off if a student has available balance in his/her identity card and SMS will be sent to students about remaining balance in their cards by GSM technology. The programming for controller is done by using proton IDE language. The SSB is the customized idea of vending machine and it attempts to resolve various issues that appeared in coin/note based VM. The student identity card RFID based technology is a breakthrough towards a paperless and cashless environment. Moreover, it is very beneficial in saving the precious time of students due to fast paced life and also user friendly. RFID based SSB also improved the communication and sensing capabilities of VM. Hence, our suggested approach outperforms in all aspects.

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Symmetric seven–stages multistep perfect in phase embedded pairs (S7S2mSEMB)

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AIP Conference Proceedings 2020年第1期2293卷

作者： Junjie Huang Junlai Qiu T. E. Simos ∗School of Computing Neusoft Institute of Guangdong Foshan 528225 China †Department of Mathematics College of Sciences King Saud University P. O. Box 2455 Riyadh 11451 Saudi Arabia Department of Automation Engineering Section of Mathematics Department of Civil Engineering Democritus University of Thrace Xanthi Greece (Visiting Professor)

A symmetric seven–stages multistep perfect in phase family of pairs is introduced in this paper. The basis for the development of the specific embedded pair is the disappearance of the phase–lag and its derivatives of order which is the maximum possible. We note that on this newly introduced family the phase–lag is considered on the whole multistage *** analyze the newly introduced family of methods by (a) studying the phase–lag and its derivatives, (b) investigating the the local truncation error (LTE) of the family and (c) considering the conditions for non empty interval of periodicity and the conditions for maximum stability *** test the effectiveness of the newly introduced family of pairs by applying it to several periodic initial and/or boundary-value problems.

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A quantitative study of using Cisco Packet Tracer simulation software to improve IT students’ creativity and outcomes

A quantitative study of using Cisco Packet Tracer simulation...

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International Conference on Cognitive Infocommunications (CogInfoCom)

作者： Robert Demeter Attila Kovari Jozsef Katona Ilona Heldal Cristina Costescu Adrian Rosan Andrea Hathazi Serge Thill Department of Automation and Information Technology Faculty of Electrical Engineering and Computer Science Transilvania University of Brasov Brasov Romania CogInfoCom Based LearnAbility Research Team Institute of Engineering Engineering University of Dunaujvaros Dunaujvaros Hungary Institute of Computer Engineering University of Dunaujvaros Dunaujvaros Hungary Department of Computing Mathematics and Physics Western Norway University of Applied Sciences Bergen Norway Special Education Department Babes-Bolyai University Cluj-Napoca Romania Donders Centre for Cognition Donders Institute for Brain Cognition and Behaviour Radboud University Nijmegen Netherland

ISBN: (数字)9781728147932

ISBN: (纸本)9781728147949

The continued development of ICT technologies has led to new ways of information communication. As is well known, the success of any new training or communication technology incorporates disseminating information, timeliness and efficiency and often incorporates simulation and virtual reality technologies. This paper presents the results of a quantitative study showing that simulation-based training strategies are more effective than traditional methods. The current case is for applying didactic teaching methodologies for learning ICT concepts for complex systems. The paper also compares the results of this study with previous studies and recommends strategies for using virtual reality elements to streamline learning process of engineering students.

关键词： Computer networks Software Tools Education Hardware Intelligent sensors

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HMM-Based $\mathcal{H}_{\infty}$ Filtering for Discrete-Time Markov Jump LPV Systems Over Unreliable Communication Channels

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IEEE Transactions on Systems, Man, and Cybernetics: Systems 2018年第12期48卷 2035-2046页

作者： Yanzheng Zhu Zhixiong Zhong Wei Xing Zheng Donghua Zhou College of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao China Department of Mechanical Engineering University of Victoria Victoria BC Canada School of Computing Engineering and Mathematics Western Sydney University Sydney NSW Australia

In this paper, the filtering problem is investigated for a class of discrete-time Markov jump linear parameter varying systems with packet dropouts and channel noises in the network surroundings. The partial accessibility of system modes with respect to the designed filter is described by a hidden Markov model (HMM). A typical behavior characterization mechanism is proposed in the communication channel including data losses and additive noises, which occurs in a probabilistic way based on two mutually independent Bernoulli sequences. With the aid of a class of Lyapunov function subject to parameter-dependent and mode-dependent constraints, sufficient conditions ensuring the existence of HMM-based filters are obtained such that the filtering error system is stochastically stable with a guaranteed H ∞ error performance. The influence of monotonicity on the performance index is explored while changing the degree of both additive noise and mode inaccessibility. The effectiveness and applicability of the obtained results are finally verified by two numerical examples.

关键词： Hidden Markov models Markov processes Communication channels Additive noise Pollution measurement Noise measurement Symmetric matrices

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Recording Eye-tracking Parameters during a Program Source-code Debugging Example

Recording Eye-tracking Parameters during a Program Source-co...

引用

International Conference on Cognitive Infocommunications (CogInfoCom)

作者： Jozsef Katona Attila Kovari Ilona Heldal Carsten Helgesen Cristina Costescu Adrian Rosan Andrea Hathazi Serge Thill Robert Demeter CogInfoCom Based LearnAbility Research Team Institute of Computer Engineering University of Dunaujvaros Dunaujvaros Hungary Institute of Engineering University of Dunaujvaros Dunaujvaros Hungary Department of Computing Mathematics and Physics Western Norway University of Applied Sciences Bergen Norway Special Education Department Faculty of Psychology and Educational Sciences Babes- Bolyai University Cluj-Napoca Romania Cognition and Behaviour Radboud University Nijmegen Netherland Department of Automation and Information Technology Faculty of Electrical Engineering and Computer Science Transilvania University of Brasov Brasov Romania

ISBN: (数字)9781728147932

ISBN: (纸本)9781728147949

Recently, researches based on eye-tracking have more often appeared on the field of cognitive studies, education support systems and virtual reality. Eye-tracking based analysis may be useful in IT, particular in algorithm thinking, program code debugging. The purpose of this paper is to introduce the conditions of Gazepoint GP3 device and OGAMA used to record eye-motion parameters and demonstrate the recording process and steps.

关键词： Conferences Testing Software Debugging Education Cognition Three-dimensional displays

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