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A Lane-Changing Trajectory Planning and Assistant Decision-Making Method for Autonomous Vehicle 18

A Lane-Changing Trajectory Planning and Assistant Decision-M...

18th COTA International Conference of Transportation Professionals: Intelligence, Connectivity, and Mobility, CICTP 2018

作者： Cui, Zheyu Hu, Jianming Guan, Hongfei School of Computer Science Beijing Univ. of Posts and Telecommunications Beijing100876 China Dept. of Automation Tsinghua Univ. TNList Beijing100084 China Key Laboratory of Space Utilization Technology and Engineering Center for Space Utilization Chinese Academy of Sciences Beijing100094 China

ISBN: (数字)9780784481523

ISBN: (纸本)9780784481523

Aiming at shortcomings of the traditional decision-making models for lane changing, such as only considering the nearest time gaps, and using static gap models, overlook the dynamic characteristic of vehicles' gap. A new lane-changing decision-making model is put forward based on dynamic gap. By adopting an approach of dept.-first search and the designed satisfactory function, the gap that meets the most satisfaction is selected for lanes changing. The second model uses the constraint optimization model on the basis of the gap obtained by the previous model. It then uses the primal dual interior point method based on the second order cone programming (SOCP) to obtain the optimal trajectory, after considering the comfort and traffic flow. Finally, the correctness, robustness, and linkage of the two models are verified through the design of typical lane changing scenarios and simulation experiments. © 2018 American Society of Civil Engineers.

关键词： Second-order cone programming

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IoT Forensic A digital investigation framework for IoT systems

IoT Forensic A digital investigation framework for IoT syste...

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International Conference on Electronics, computers and Artificial Intelligence (ECAI)

作者： Snehal Sathwara Nitul Dutta Emil Pricop computer Engineering Department Marwadi University Rajkot Gujarat India Automation Computers & Electronics Dept. Petroleum-Gas University of Ploiesti Ploiesti Romania

ISBN: (纸本)9781538649022;9781538649015

Security issues, threats, and attacks in relation with the IoT have been identified as promising and challenging area of research. Eventually, the need for a forensics methodology for investigating IoT -related crime is therefore essential. However, the IoT poses many challenges for forensics investigators. These include the wide range and variety of information, the unclear lines of differentiation between networks, for example private networks increasingly fading into public networks. Further, integration of a large number of objects in IoT forensic interest, along with the relevance of identified and collected devices makes forensic of IoT devices more complicated. The scope of this paper is to present a framework for IoT forensic. We aimed at the study and development of the link to support digital investigations of IoT devices and tackle emerging challenges in digital forensics. We emphasize on various steps for digital forensic with respect to IoT devices.

关键词： Digital forensics computer hacking Ecosystems Sensors Protocols

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Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challenge

arXiv

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arXiv 2022年

作者： Ali, Sharib Ghatwary, Noha Jha, Debesh Isik-Polat, Ece Polat, Gorkem Yang, Chen Li, Wuyang Galdran, Adrian Ballester, Miguel-Ángel González Thambawita, Vajira Hicks, Steven Poudel, Sahadev Lee, Sang-Woong Jin, Ziyi Gan, Tianyuan Yu, ChengHui Yan, JiangPeng Yeo, Doyeob Lee, Hyunseok Tomar, Nikhil Kumar Haithmi, Mahmood Ahmed, Amr Riegler, Michael A. Daul, Christian Halvorsen, Pål Rittscher, Jens Salem, Osama E. Lamarque, Dominique Cannizzaro, Renato Realdon, Stefano de Lange, Thomas East, James E. Institute of Biomedical Engineering Department of Engineering Science University of Oxford OxfordOX3 7DQ United Kingdom Oxford National Institute for Health Research Biomedical Research Centre OxfordOX4 2PG United Kingdom Big Data Institute University of Oxford Li Ka Shing Centre for Health Information and Discovery OxfordOX3 7LF United Kingdom Translational Gastroenterology Unit Nuffield Department of Medicine Experimental Medicine Div. John Radcliffe Hospital University of Oxford OxfordOX3 9DU United Kingdom Computer Engineering Department Arab Academy for Science and Technology Alexandria1029 Egypt SimulaMet Oslo0167 Norway Department of Computer Science UiT The Arctic University of Norway Hansine Hansens veg 18 Tromsø9019 Norway Medical Department Sahlgrenska University Hospital-Mölndal Blå stråket 5 Göteborg413 45 Sweden Veneto Institute of Oncology IOV-IRCCS Via Gattamelata 64 Padua35128 Italy CRO Centro Riferimento Oncologico IRCCS Aviano Italy Via Franco Gallini 2 PN Aviano33081 Italy Université de Versailles St-Quentin en Yvelines Hôpital Ambroise Paré 9 Av. Charles de Gaulle Boulogne-Billancourt92100 France Faculty of Medicine University of Alexandria Alexandria21131 Egypt Graduate School of Informatics Middle East Technical University Ankara06800 Turkey City University of Hong Kong Kowloon Hong Kong BCN MedTech Dept. of Information and Communication Technologies Universitat Pompeu Fabra Barcelona08018 Spain Department of IT Convergence Engineering Gachon University Seongnam13120 Korea Republic of College of Biomedical Engineering and Instrument Science Zhejiang University Hangzhou310027 China Tsinghua Shenzhen International Graduate School Tsinghua University Shenzhen518055 China Department of Automation Tsinghua University Beijing100084 China Smart Sensing & Diagnosis Research Division Korea Atomic Energy Research Institute 34057 Korea Republic of Daegu-Gyeongbuk Medical Innovation Foundation Medical Device Deve

Polyps are well-known cancer precursors identified by colonoscopy. However, variability in their size, location, and surface largely affect identification, localisation, and characterisation. Moreover, colonoscopic surveillance and removal of polyps (referred to as polypectomy) are highly operator-dependent procedures. There exist a high missed detection rate and incomplete removal of colonic polyps due to their variable nature, the difficulties to delineate the abnormality, the high recurrence rates, and the anatomical topography of the colon. There have been several developments in realising automated methods for both detection and segmentation of these polyps using machine learning. However, the major drawback in most of these methods is their ability to generalise to out-of-sample unseen datasets that come from different centres, modalities and acquisition systems. To test this hypothesis rigorously we curated a multi-centre and multi-population dataset acquired from multiple colonoscopy systems and challenged teams comprising machine learning experts to develop robust automated detection and segmentation methods as part of our crowd-sourcing Endoscopic computer vision challenge (EndoCV) 2021. In this paper, we analyse the detection results of the four top (among seven) teams and the segmentation results of the five top teams (among 16). Our analyses demonstrate that the top-ranking teams concentrated on accuracy (i.e., accuracy > 80% on overall Dice score on different validation sets) over real-time performance required for clinical applicability. We further dissect the methods and provide an experiment-based hypothesis that reveals the need for improved generalisability to tackle diversity present in multi-centre datasets. © 2022, CC BY-NC-SA.

关键词： Endoscopy

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De-Noising Using Dual Threshold Function For Speaker Recognition At Low SNR

De-Noising Using Dual Threshold Function For Speaker Recogni...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Haiyan Yang Ping Zhou Tatsuki Fukuda Hua-An Zhao Information and Communication School Guilin University of Electronic Technology China School of Electronic Engineering and Automation Guilin University of Electronic Technology China Dept. of Creative Engineering National Institute of Technology Kitakyushu College Japan Dept. of Computer Science and Electrical Engineering Kumamoto University Japan

In recent years, speaker recognition as biometric authentication has been attracting attention. In automatic speaker recognition system, there are some key steps such as de-noising, feature extraction, creating speaker models and machine learning. Feature extraction is one of the most important processes for improving the accuracy of the speaker recognition. However, the performance of feature extraction is reduced by impact of noise. Especially, the noise influence is large at low SNR. In this paper, we propose a new method for de-noising method using a dual threshold reduction function. At low SNR environment, the proposed method has good performances compare with other threshold function methods.

关键词： Speaker recognition Feature extraction Noise reduction IIR filters Signal to noise ratio Finite impulse response filters

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Fish-Eye Lenses-Based Camera Calibration and Panoramic Image Stitching 5

Fish-Eye Lenses-Based Camera Calibration and Panoramic Image...

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5th IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2018

作者： Hsu, Chao-Yung Chang, Chih-Ming Kang, Li-Wei Kang Fu, Ru-Hong Chen, Duan-Yu Weng, Ming-Fang Automation Instrumentation System Development Sec. China Steel Corporation Kaohsiung Taiwan New Smart Technology Co. LTD. Taipei Taiwan Graduate School of Engineering Science and Technology Dept. Computer Science and Information Engineering National Yunlin University of Science and Technology Yunlin Taiwan Department of Electrical Engineering Yuan Ze University Taoyuan Taiwan Institute for Information Industry Smart Network System Institute Taiwan

ISBN: (纸本)9781538663011

Fish-eye lenses are common in several computer vision applications, such as four-camera surround view driver assistance, where a very wide angle (e.g., 180 degrees) of view is available. Nevertheless, their applicability is usually limited by the lack of an accurate and easy-to-use calibration procedure. In this paper, we present a camera calibration method for fish-eye lenses and a panoramic image stitching framework for calibrated surround images. To achieve the calibration of fish-eye captured images, it only requires to observe a reference planar pattern (e.g., chessboard), followed by offline estimating extrinsic and intrinsic parameters and save the related parameters. Each fish-eye distorted image can then be efficiently online corrected. Then, each calibrated image is transformed to its top-down view (or bird's-eye view) via the perspective transformation based on the estimated homography matrix. As a result, these surround bird'seye view images can be stitched to generate the final panoramic image. It is expected that the proposed framework would be applicable to AVM (around view monitoring) system or ADAS (advanced driver assistance system) of vehicles in the future. © 2018 IEEE.

关键词： Calibration

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Closed Loop Fault Detectability Based on a Gap-Metric

Closed Loop Fault Detectability Based on a Gap-Metric

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Control Technology and Applications (CCTA),

作者： André Sekunda Steven Ding Niels Kjølstad Poulsen Henrik Niemann Department of Electrical Engineering Automation and Control Tech. University of Denmark Denmark Dept. of Automatic Control and Complex Systems University of Duisburg-Essen Duisburg Germany Dept. of Applied Mathematics and Computer Science Tech. University of Denmark Kgs. Lyngby Denmark

Systems are often controlled using feedback loops. Fault diagnosis schemes are usually designed assuming that there is no feedback loop. Therefore fault diagnosis methods need to accommodate for the feedback loop. One such method is active fault diagnosis based on a fault signature system. This method is derived using the YJBK parametrisation, named after Youla, Jabr, Bongiorno and Kucera. It uses the derived fault signature system to determine the detectability of possible faults in the system. Deriving the fault signature system requires knowledge about the controller. This paper demonstrates the possibility of estimating the detectability of faults in the fault signature system using a gap-metric. The gap-metric has the advantage of only requiring knowledge about the plant. By using the gap-metric it is possible to estimate the detectability of faults without using information about the controller.

关键词： Fault diagnosis Measurement Kernel Closed loop systems Fault detection Sensors

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Prima: Probabilistic Ranking with Inter-Item Competition and Multi-Attribute Utility Function

Prima: Probabilistic Ranking with Inter-Item Competition and...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Qingming Li Zhanjiang Chen H. Vicky Zhao Yan Lindsay Sun Dept. of Automation Tsinghua Univ. State Key Lab of Intelligent Tech. & Sys. Tsinghua National Laboratory for Info. Sci. and Tech. Beijing P.R. China Dept. of Electrical Computer and Biomedical Engineering Univ. of Rhode Island USA

ISBN: (纸本)9781538646595

This paper proposes PRIMA: Probabilistic Ranking with Inter-item competition and Multi-Attribute utility function, which ranks items based on their probabilities of being a user's best choice. This framework is particularly important in E-commerce applications for making recommendations, predicting sales, and developing pricing strategies. To achieve mathematical tractability, it uses the weight-based multi-attribute utility function to address the inter-attribute tradeoff, where the weight reflects a user's personal preference for each attribute. The proposed work updates the weight from a user's past transactions using the concept of marginal rate of substitution from microeconomics, addresses the interitem competition, and computes the items' probabilities of being a user's best choice. Real user test results show that the proposed framework achieves comparable ranking accuracy to the state-of-the-art work with significant improvements in model simplicity and mathematical tractability.

关键词： Computational modeling Upper bound Probabilistic logic Microeconomics Two dimensional displays Estimation Analytical models

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Removed: VitSeg: Weakly supervised vitiligo segmentation in skin image

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computerized medical imaging and graphics : the official journal of the computerized Medical Imaging Society 2020年 85卷 101779页

作者： Zhangxing Bian Siyu Xia Chao Xia Ming Shao Key Laboratory of Measurement and Control of CSE Ministry of Education School of Automation Southeast University Nanjing China Electrical Engineering and Computer Science University of Michigan Ann Arbor MI USA. Electronic address: jasonbian.zx@***. Key Laboratory of Measurement and Control of CSE Ministry of Education School of Automation Southeast University Nanjing China. Electronic address: xsy@***. School of Electronics Information and Electrical Engineering ShangHai Jiao Tong University Shanghai China. Electronic address: xiabc612@***. Dept. of Computer and Information Science University of Massachusetts Dartmouth Dartmouth MA USA. Electronic address: mshao@umassd.edu.

This article has been removed: please see Elsevier Policy on Article Withdrawal (https://***/about/our-business/policies/article-withdrawal). This article has been removed at the request of the Authors and Editor-in-Chief because complete consent was not obtained by the authors in accordance with journal policy prior to publication. The authors and the journal sincerely apologize for this oversight.

关键词： Convolutional neural network Saliency propagation Skin lesion Vitiligo Weakly supervised segmentation

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Prediction of preterm infant mortality with Gaussian process classification 25

Prediction of preterm infant mortality with Gaussian process...

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25th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2017

作者： Rinta-Koski, Olli-Pekka Särkkä, Simo Hollmén, Jaakko Leskinen, Markus Andersson, Sture Aalto University Department of Computer Science Espoo Finland Aalto University Dept. of Electrical Engineering and Automation Espoo Finland University of Helsinki Helsinki University Hospital Helsinki Finland

ISBN: (纸本)9782875870391

We present a method for predicting preterm infant inhospital- mortality using Bayesian Gaussian process classification. We combined features extracted from sensor measurements, made during the first 24 hours of care for 581 Very Low Birth Weight infants, with standard clinical features calculated on arrival at the Neonatal Intensive Care Unit. We achieved a classification result with area under curve of 0.94 (standard error 0.02), which is in excess of the results achieved by using the clinical standard SNAP-II and SNAPPE-II scores. © ESANN 2017 - Proceedings, 25th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. All rights reserved.

关键词： Gaussian noise (electronic)

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Robotic applications in the automation of agricultural production under greenhouse: A review 3

Robotic applications in the automation of agricultural produ...

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3rd IEEE Colombian Conference on Automatic Control, CCAC 2017

作者： Tangarife, Hector Ivan Diaz, Andres Escobar CMM Investigation Group GICEMET SENA Dept. Electronic. Spe. Computer Science and Automation District University FJC Bogotá Colombia Investigation Group ORCA Dept. Control Engineering and Telecommunications District University Francisco José de Caldas Bogotá Colombia

ISBN: (纸本)9781538603987

This article shows a review of the state of the art in the agricultural automation under greenhouse through the use of robotics platforms as a source of solution to different problems that arise in the agricultural sector specially under controlled conditions;the writing is part of a wide review of the agricultural automation under greenhouse and a set of proposals that consider applications in various fields of research, autonomous localized irrigation, neural networks, automatic learning, monitoring and control systems among others. It is intended to determine the most recent advances in techniques for sowing, applications of chemical for sanitary control, fertilization, harvest, where robotics is used as a source to solve agricultural problems. The review includes consultation in well-known national and international journals, research carried out in centers and research groups or companies dedicated to implementation addressed to the agricultural sector, finally it is determined the solutions that can be implemented to propose new topics, research lines, development and technology transfer to the agricultural sector. © 2017 IEEE.

关键词： Greenhouses

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