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Conference on computer Vision and Pattern Recognition (CVPR)

作者： M. Eisenmann A. Reinke V. Weru M. D. Tizabi F. Isensee T. J. Adler S. Ali V. Andrearczyk M. Aubreville U. Baid S. Bakas N. Balu S. Bano J. Bernal S. Bodenstedt A. Casella V. Cheplygina M. Daum M. De Bruijne A. Depeursinge R. Dorent J. Egger D. G. Ellis S. Engelhardt M. Ganz N. Ghatwary G. Girard P. Godau A. Gupta L. Hansen K. Harada M. Heinrich N. Heller A. Hering A. Huaulmé P. Jannin A. E. Kavur O. Kodym M. Kozubek J. Li H. Li J. Ma C. Martín-Isla B. Menze A. Noble V. Oreiller N. Padoy S. Pati K. Payette T. Rädsch J. Rafael-Patiño V. Singh Bawa S. Speidel C. H. Sudre K. Van Wijnen M. Wagner D. Wei A. Yamlahi M. H. Yap C. Yuan M. Zenk A. Zia D. Zimmerer D. Aydogan B. Bhattarai L. Bloch R. Brüngel J. Cho C. Choi Q. Dou I. Ezhov C. M. Friedrich C. Fuller R. R. Gaire A. Galdran Á. García Faura M. Grammatikopoulou S. Hong M. Jahanifar I. Jang A. Kadkhodamohammadi I. Kang F. Kofler S. Kondo H. Kuijf M. Li M. Luu T. Martinčič P. Morais M. A. Naser B. Oliveira D. Owen S. Pang J. Park S. Park S. Płotka E. Puybareau N. Rajpoot K. Ryu N. Saeed A. Shephard P. Shi D. Štepec R. Subedi G. Tochon H. R. Torres H. Urien J. L. Vilaça K. A. Wahid H. Wang J. Wang L. Wang X. Wang B. Wiestler M. Wodzinski F. Xia J. Xie Z. Xiong S. Yang Y. Yang Z. Zhao K. Maier-Hein P. F. Jäger A. Kopp-Schneider L. Maier-Hein Division of Intelligent Medical Systems German Cancer Research Center (DKFZ) Heidelberg Germany Helmholtz Imaging German Cancer Research Center (DKFZ) Heidelberg Germany Faculty of Mathematics and Computer Science Heidelberg University Heidelberg Germany Division of Biostatistics German Cancer Research Center (DKFZ) Heidelberg Germany Division of Medical Image Computing German Cancer Research Center (DKFZ) Heidelberg Germany Faculty of Engineering and Physical Sciences School of Computing University of Leeds Leeds UK Institute of Informatics School of Management HES-SO Valais-Wallis University of Applied Sciences and Arts Western Switzerland Sierre Switzerland Department of Nuclear Medicine and Molecular Imaging Lausanne University Hospital Lausanne Switzerland Technische Hochschule Ingolstadt Ingolstadt Germany Center for Artificial Intelligence and Data Science for Integrated Diagnostics (AI2D) and Center for Biomedical Image Computing and Analytics (CBICA) University of Pennsylvania Philadelphia PA USA Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Department of Radiology Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Department of Radiology University of Washington Seattle WA USA Department of Computer Science Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS) University College London London UK Universitat Autònoma de Barcelona & Computer Vision Center Barcelona Spain Division of Translational Surgical Oncology National Center for Tumor Diseases (NCT/UCC) Dresden Dresden Germany Department of Advanced Robotics Istituto Italiano di Tecnologia Italy Department of Electronics Information and Bioengineering Politecnico di Milano Milan Italy IT University of Copenhagen Copenhagen Denmark Department of General Visceral and Transplantation Surgery Heidelberg University Hospital Heidelberg Germany Department of Radiology and Nuc

International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to investigating what can be learnt from these competitions. Do they really generate scientific progress? What are common and successful participation strategies? What makes a solution superior to a competing method? To address this gap in the literature, we performed a multicenter study with all 80 competitions that were conducted in the scope of IEEE ISBI 2021 and MICCAI 2021. Statistical analyses performed based on comprehensive descriptions of the submitted algorithms linked to their rank as well as the underlying participation strategies revealed common characteristics of winning solutions. These typically include the use of multi-task learning (63%) and/or multi-stage pipelines (61%), and a focus on augmentation (100%), image preprocessing (97%), data curation (79%), and post-processing (66%). The “typical” lead of a winning team is a computer scientist with a doctoral degree, five years of experience in biomedical image analysis, and four years of experience in deep learning. Two core general development strategies stood out for highly-ranked teams: the reflection of the metrics in the method design and the focus on analyzing and handling failure cases. According to the organizers, 43% of the winning algorithms exceeded the state of the art but only 11% completely solved the respective domain problem. The insights of our study could help researchers (1) improve algorithm development strategies when approaching new problems, and (2) focus on open research questions revealed by this work.

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The 5th International Conference on Biomedical Engineering and Biotechnology (ICBEB 2016) Abstracts

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BMC MEDICAL IMAGING 2016年第SUPPL 1期16卷 65-65页

作者： [Anonymous] Department of MRI Shandong Medical Imaging Research Institute Affiliated to Shandong University Jinan Shandong 250021 People’s Republic of China Department of Interventional Radiology Shandong Provincial Hospital Affiliated to Shandong University Jinan Shandong 250021 People’s Republic of China College of Information Science and Technology Engr. Research Center of Digitized Textile & Fashion Tech. for Ministry of Education Donghua University Shanghai 201620 China Intelligent multimedia information processing Lab College of Software Northeastern University Shenyang Liaoning Province 110004 China Institute of Biomedical and Health Engineering Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China School of Computer Science and Technology Nanjing Normal University Nanjing China Department of Electrical Engineering The City College of New York CUNY New York USA Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing Nanjing China School of Electronic Science and Engineering Nanjing University Nanjing Jiangsu 210046 China College of Engineering Nanyang Technological University Singapore 639798 Singapore School of Electronic Information Shanghai Dianji University Shanghai China School of Natural Sciences and Mathematics Shepherd University Shepherdstown WV 25443 USA Davis College of Agriculture Natural Resources and Design West Virginia University Morgantown WV 26505 USA State Key Laboratory of Millimeter Waves Southeast University Nanjing 210096 China Center of Medical Physics and Technology Hefei Institutes of Physical Science Chinese Academy of Sciences Hefei China College of Agricultural and Life Sciences University of Florida Gainesville FL 32611 USA Courant Institute of Mathematical Sciences New York University New York NY 10012 USA Translational Imaging Division & MRI Unit Columbia University and New York State Psychiatric Institute New York NY 10032 USA Guangxi Key Laboratory of Manufacturing System & Adv

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A Valid Frequency Range Analysis of Throat Signal for Voice Command System

A Valid Frequency Range Analysis of Throat Signal for Voice ...

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International Conference on information Science and Applications (ICISA)

作者： Young-Giu Jung Mun-Sung Han Kyung-Yong Chung Sang Jo Lee Multimodal & Human Interaction Laboratory MY-Nail Tech Incheon South Korea Robot/Cognition System Research Department Electronics and Telecommunications Research Institute Daejeon South Korea School of Computer Information Engineering Sangji University Wonju South Korea Language&Information Processing Kyungpook National University Daegu South Korea

ISBN: (纸本)9781424492220

In this paper, a valid frequency range of throat signal analyses is presented. Compare to speech signals, the throat signals have many differences in the amount of information. In this context, targeting on throat signals to find valid frequency range is one of the most important analyses for the development of new breed of feature extraction algorithm. In this respect, using analysis similarity of throat signals feature distribution and correlation analysis of throat signals in the frequency domain, the frequency range can be found with effective and quick response time to be applied to a voice command recognition system using neck-microphone. As a result, the proposed frequency range is from 200Hz (center frequency) to 2001Hz (center frequency). For the neck-microphone voice command system using the proposed frequency range, a significant reduction in time complexity of 25% can be achieved without any loss in recognition rate.

关键词： Feature extraction Microphones Correlation Speech recognition Band pass filters Finite impulse response filter Indexes

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Generating high-coverage semantic orientation lexicons from overtly marked words and a thesaurus

Generating high-coverage semantic orientation lexicons from ...

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2009 Conference on Empirical Methods in Natural Language processing, EMNLP 2009, Held in Conjunction with ACL-IJCNLP 2009

作者： Mohammad, Saif Dunne, Cody Dorr, Bonnie Laboratory for Computational Linguistics and Information Processing University of Maryland United States Human-Computer Interaction Lab. University of Maryland United States Institute for Advanced Computer Studies University of Maryland United States Department of Computer Science University of Maryland United States Human Language Technology Center of Excellence United States

Sentiment analysis often relies on a semantic orientation lexicon of positive and negative words. A number of approaches have been proposed for creating such lexicons, but they tend to be computationally expensive, and usually rely on significant manual annotation and large corpora. Most of these methods use WordNet. In contrast, we propose a simple approach to generate a high-coverage semantic orientation lexicon, which includes both individual words and multi-word expressions, using only a Roget-like thesaurus and a handful of affixes. Further, the lexicon has properties that support the Polyanna Hypothesis. Using the General Inquirer as gold standard, we show that our lexicon has 14 percentage points more correct entries than the leading WordNet-based high-coverage lexicon (SentiWordNet). In an extrinsic evaluation, we obtain significantly higher performance in determining phrase polarity using our thesaurus-based lexicon than with any other. Additionally, we explore the use of visualization techniques to gain insight into the our algorithm beyond the evaluations mentioned above. © 2009 ACL and AFNLP.

关键词： Thesauri

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Generating high-coverage semantic orientation lexicons from overtly marked words and a thesaurus 09

Generating high-coverage semantic orientation lexicons from ...

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Proceedings of the 2009 Conference on Empirical Methods in Natural Language processing: Volume 2 - Volume 2

作者： Saif Mohammad Cody Dunne Bonnie Dorr Laboratory for Computational Linguistics and Information Processing and Institute for Advanced Computer Studies and Human Language Technology Center of Excellence Human-Computer Interaction Lab and University of Maryland Laboratory for Computational Linguistics and Information Processing and Institute for Advanced Computer Studies and University of Maryland and Human Language Technology Center of Excellence

ISBN: (纸本)9781932432626

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Vision based environment recognition and movement control for autonomous wheeled mobile robots

Vision based environment recognition and movement control fo...

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IEEE International Conference on Mechatronics and Automation

作者： Gen'ichi Yasuda Bin Ge Department of Human and Computer Intelligence Nagasaki Institute of Applied Science Nagasaki Japan Liao Ning Key Laboratory of Intelligent Information Processing Economic & Technical Development Zone Dalian University Dalian China

This paper presents an experimental study on environment recognition and movement control for multiagent robotic soccer using wheeled mobile robots. A color image segmentation method based on YUV color information of each pixel of the color image is applied to the object recognition. The color image segmentation is performed using the tables that transform each value in a pixel to membership in several color classes, where the lower and higher threshold values of Y, U, and V are determined and described for the sample color markers. The position of objects on the field is efficiently and accurately calculated using a monocular camera. A common image processing method is used to detect landmarks such as corners/edges in the environment. A movement control algorithm is implemented based on the distance and orientation to the target. Experimental results of real-time movement control are also presented.

关键词： Mobile robots Robot vision systems Color Image processing Wheels Cameras Control systems Object recognition Image segmentation Pixel

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Tangible augmented user interface for interactive simulation of the jaw motion

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Journal of information and Computational Science 2008年第5期5卷 2071-2076页

作者： Ji, Lianen Lu, You Zhang, Fengjun Department of Computer Science and Technology China University of Petroleum Beijing 102249 China Laboratory of Human-Computer Interaction and Intelligent Information Processing Institute of Software Chinese Academy of Sciences Beijing 100080 China

This paper presents a novel 3D interactive system for simulation and visualization of the human jaw motion. Based on the visual tracking technique, teeth plaster cast and marker cards is used for manipulating virtual teeth model and controlling the simulation of jaw motion. Through introducing their interactive semantic attributes, these physical interface elements are classified into various interaction types. Furthermore, various interaction tasks and techniques are seamlessly merged into a uniform interface framework, which integrates physical space with virtual space together. This innovative 3D interface can effectively exploit the dentist's existing skills and provide more intuitive and natural 3D interaction techniques than traditional ones. 1548-7741/Copyright © 2008 Binary information Press October 2008.

关键词： Augmented reality

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Model driven development method for interactive information visualization

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Ruan Jian Xue Bao/Journal of Software 2008年第8期19卷 1947-1964页

作者： Ren, Lei Wang, Wei-Xin Zhou, Ming-Jun Teng, Dong-Xing Ma, Cui-Xia Dai, Guo-Zhong Wang, Hong-An Laboratory of Human-Computer Interaction and Intelligent Information Processing Institute of Software Chinese Academy of Sciences Beijing 100190 China

Wide-Spread deployment for interactive information visualization is difficult. Non-Specialist users need a general development method and a toolkit to support the generic data structures suited to tree, network and multi-dimensional data, special visualization techniques and interaction techniques, and well-known generic information tasks. This paper presents a model driven development method for interactive information visualization. First, an interactive information visualization interface model (IIVM) is proposed. Then, the development method for interactive information visualization based on IIVM is presented. The Daisy toolkit is introduced, which includes Daisy model builder, Daisy IIV generator and runtime framework with Daisy library. Finally, an application example is given. Experimental results show that Daisy can provide a general solution for development for interactive information visualization.

关键词： User interfaces

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一种肤色干扰下的变形手势跟踪方法

一种肤色干扰下的变形手势跟踪方法

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第六届智能CAD与数字娱乐学术会议

作者： Liu Yujin 刘玉进 Cai Yong 蔡勇 Wu Huiyue 武汇岳 Zhang Fengjun 张凤军 Dai Guozhong 戴国忠 School of Computer Science and Technology Southwest University of Science and Technology Mianyang 西南科技大学计算机科学与技术学院绵阳 621002 中国科学院软件研究所人机交互技术与智能信息处理实验室北京 100190 School of Computer Science and Technology Southwest University of Science and Technology Mianyang 西南科技大学计算机科学与技术学院绵阳 621002 Laboratory of Human-Computer Interaction and Intelligent Information Processing Institute of Softwa 中国科学院软件研究所人机交互技术与智能信息处理实验室北京 100190

本文介绍了一种基于单目视觉的肤色干扰下的变形手势跟踪方法。根据跟踪过程中所用到的基本手势特征，提出了一种基于PGH(成对几何直方图)的静态手势识别方法。为了解决跟踪过程中的肤色干扰问题，实现了基于Kalman滤波器的手势预测跟... 详细信息

本文介绍了一种基于单目视觉的肤色干扰下的变形手势跟踪方法。根据跟踪过程中所用到的基本手势特征，提出了一种基于PGH(成对几何直方图)的静态手势识别方法。为了解决跟踪过程中的肤色干扰问题，实现了基于Kalman滤波器的手势预测跟踪。为了解决跟踪过程中的初始化问题，提出了一种基于层次结构的跟踪初始化解决方案。实验结果表明，该方法能够在肤色干扰的情况下有效地对变形手势进行跟踪，并能够满足基于视觉的实时人机交互的要求。

关键词：手势识别变形手势肤色干扰视觉跟踪

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Evaluating tagging behavior in social bookmarking systems: Metrics and design heuristics 07

Evaluating tagging behavior in social bookmarking systems: M...

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2007 International ACM Conference on Supporting Group Work, GROUP'07

作者： Farooq, Umer Kannampallil, Thomas G. Song, Yang Ganoe, Craig H. Carroll, John M. Giles, Lee Computer-Supported Collaboration and Learning Laboratory Center for Human-Computer Interaction United States Intelligent Systems Research Laboratory College of Information Sciences and Technology Pennsylvania State University University Park PA 16802 United States

ISBN: (纸本)9781595938459

To improve existing social bookmarking systems and to design new ones, researchers and practitioners need to understand how to evaluate tagging behavior. In this paper, we analyze over two years of data from CiteULike, a social bookmarking system for tagging academic papers. We propose six tag metrics-tag growth, tag reuse, tag non-obviousness, tag discrimination, tag frequency, and tag patterns-to understand the characteristics of a social bookmarking system. Using these metrics, we suggest possible design heuristics to implement a social bookmarking system for CiteSeer, a popular online scholarly digital library for computer science. We believe that these metrics and design heuristics can be applied to social bookmarking systems in other domains. © 2007 ACM.

关键词： Digital libraries

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