检索结果-内蒙古大学图书馆

BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets

学校读者我要写书评

暂无评论

Nature methods 2023年第6期20卷 824-835页

作者： Linus Manubens-Gil Zhi Zhou Hanbo Chen Arvind Ramanathan Xiaoxiao Liu Yufeng Liu Alessandro Bria Todd Gillette Zongcai Ruan Jian Yang Miroslav Radojević Ting Zhao Li Cheng Lei Qu Siqi Liu Kristofer E Bouchard Lin Gu Weidong Cai Shuiwang Ji Badrinath Roysam Ching-Wei Wang Hongchuan Yu Amos Sironi Daniel Maxim Iascone Jie Zhou Erhan Bas Eduardo Conde-Sousa Paulo Aguiar Xiang Li Yujie Li Sumit Nanda Yuan Wang Leila Muresan Pascal Fua Bing Ye Hai-Yan He Jochen F Staiger Manuel Peter Daniel N Cox Michel Simonneau Marcel Oberlaender Gregory Jefferis Kei Ito Paloma Gonzalez-Bellido Jinhyun Kim Edwin Rubel Hollis T Cline Hongkui Zeng Aljoscha Nern Ann-Shyn Chiang Jianhua Yao Jane Roskams Rick Livesey Janine Stevens Tianming Liu Chinh Dang Yike Guo Ning Zhong Georgia Tourassi Sean Hill Michael Hawrylycz Christof Koch Erik Meijering Giorgio A Ascoli Hanchuan Peng Institute for Brain and Intelligence Southeast University Nanjing China. Microsoft Corporation Redmond WA USA. Tencent AI Lab Bellevue WA USA. Computing Environment and Life Sciences Directorate Argonne National Laboratory Lemont IL USA. Kaya Medical Seattle WA USA. University of Cassino and Southern Lazio Cassino Italy. Center for Neural Informatics Structures and Plasticity Krasnow Institute for Advanced Study George Mason University Fairfax VA USA. Faculty of Information Technology Beijing University of Technology Beijing China. Beijing International Collaboration Base on Brain Informatics and Wisdom Services Beijing China. Nuctech Netherlands Rotterdam the Netherlands. Janelia Research Campus Howard Hughes Medical Institute Ashburn VA USA. Department of Electrical and Computer Engineering University of Alberta Edmonton Alberta Canada. Ministry of Education Key Laboratory of Intelligent Computation and Signal Processing Anhui University Hefei China. Paige AI New York NY USA. Scientific Data Division and Biological Systems and Engineering Division Lawrence Berkeley National Lab Berkeley CA USA. Helen Wills Neuroscience Institute and Redwood Center for Theoretical Neuroscience UC Berkeley Berkeley CA USA. RIKEN AIP Tokyo Japan. Research Center for Advanced Science and Technology (RCAST) The University of Tokyo Tokyo Japan. School of Computer Science University of Sydney Sydney New South Wales Australia. Texas A&M University College Station TX USA. Cullen College of Engineering University of Houston Houston TX USA. Graduate Institute of Biomedical Engineering National Taiwan University of Science and Technology Taipei Taiwan. National Centre for Computer Animation Bournemouth University Poole UK. PROPHESEE Paris France. Department of Neuroscience Columbia University New York NY USA. Mortimer B. Zuckerman Mind Brain Behavior Institute Columbia University New York NY USA. Department of Computer Science Northern Illinois Universit

BigNeuron is an open community bench-testing platform with the goal of setting open standards for accurate and fast automatic neuron tracing. We gathered a diverse set of image volumes across several species that is representative of the data obtained in many neuroscience laboratories interested in neuron tracing. Here, we report generated gold standard manual annotations for a subset of the available imaging datasets and quantified tracing quality for 35 automatic tracing algorithms. The goal of generating such a hand-curated diverse dataset is to advance the development of tracing algorithms and enable generalizable benchmarking. Together with image quality features, we pooled the data in an interactive web application that enables users and developers to perform principal component analysis, t-distributed stochastic neighbor embedding, correlation and clustering, visualization of imaging and tracing data, and benchmarking of automatic tracing algorithms in user-defined data subsets. The image quality metrics explain most of the variance in the data, followed by neuromorphological features related to neuron size. We observed that diverse algorithms can provide complementary information to obtain accurate results and developed a method to iteratively combine methods and generate consensus reconstructions. The consensus trees obtained provide estimates of the neuron structure ground truth that typically outperform single algorithms in noisy datasets. However, specific algorithms may outperform the consensus tree strategy in specific imaging conditions. Finally, to aid users in predicting the most accurate automatic tracing results without manual annotations for comparison, we used support vector machine regression to predict reconstruction quality given an image volume and a set of automatic tracings.

关键词：

Parkes transient events: I. database of single pulses, initial results and missing frbs

学校读者我要写书评

暂无评论

arXiv 2020年

作者： Zhang, S.-B. Hobbs, G. Russell, C.J. Toomey, L. Dai, S. Dempsey, J. Manchester, R.N. Johnston, S. Staveley-Smith, L. Wu, X.-F. Li, D. Yang, Y.-Y. Wang, S.-Q. Qiu, H. Luo, R. Wang, C. Zhang, C. Zhang, L. Mandow, R. Purple Mountain Observatory Chinese Academy of Sciences Nanjing210008 China University of Chinese Academy of Sciences Beijing100049 China CSIRO Astronomy and Space Science PO Box 76 EppingNSW1710 Australia International Centre for Radio Astronomy Research University of Western Australia CrawleyWA6009 Australia CSIRO Scientific Computing Services Australian Technology Park Locked Bag 9013 AlexandriaNSW1435 Australia CSIRO Information Management & Technology Box 225 DicksonACT2602 Australia National Astronomical Observatories Chinese Academy of Sciences A20 Datun Road Chaoyang District Beijing100101 China FAST Collaboration CAS Key Laboratory of FAST NAOC Chinese Academy of Sciences Beijing100101 China School of Physics and Electronic Science Guizhou Education University Guiyang550018 China Xinjiang Astronomical Observatory Chinese Academy of Sciences Urumqi Xinjiang830011 China Sydney Institute for Astronomy School of Physics University of Sydney SydneyNSW2006 Australia CSIRO Data61 SydneyNSW2015 Australia Centre for Astrophysics and Supercomputing Swinburne University of Technology Mail H30 PO Box 218 HawthornVIC3122 Australia

A large number of observations from the Parkes 64 m-diameter radio telescope, recorded with high time resolution, are publicly available. We have re-processed all of the observations obtained during the first four years (from 1997 to 2001) of the Parkes Multibeam receiver system in order to identify transient events and have built a database that records the 568,736,756 pulse candidates generated during this search. We have discovered a new fast radio burst (FRB), FRB 010305, with a dispersion measure of 350±5 cm−3 pc and explored why so few FRBs have been discovered in data prior to 2001. After accounting for the dispersion smearing across the channel bandwidth and the sky regions surveyed, the number of FRBs is found to be consistent with model predictions. We also present five single pulse candidates from unknown sources, but with Galactic dispersion measures. We extract a diverse range of sources from the database, which can be used, for example, as a training set of data for new software being developed to search for FRBs in the presence of radio frequency interference. Copyright © 2020, The Authors. All rights reserved.

关键词： Database systems

Research on Hepatitis Auxiliary Diagnosis Model Based on Fuzzy Integral and GA-BP Neural Network

学校读者我要写书评

暂无评论

Research on Hepatitis Auxiliary Diagnosis Model Based on Fuz...

2017 IEEE 8th International Conference on Software Engineering and Service Science

作者： Chunyan Yang JinJie Song Tianjin Key Laboratory of Intelligent Computing & Novel Software Technology Tianjin University of Technology Key Laboratory of Computer Vision and System Ministry of Education Tianjin University of Technology

In this pa per, in order to impro ve the accuracy of hepatitis diagnosis in computer-aided diagnosis system, the medical data from the network public database were optimized by GA-BP neural network algorithm, and then we obtained the important index of judging the hepatitis and the weight of the index through thi s algorithm, we regarded the weight as the single point measure of non-additive, and then using the fuzzy integral calculated the proba bility of a person being diagnosed with hepatitis. From the results of calculation, using fuzzy integral can greatly improve the accuracy of hepatitis auxiliary diagnosis.

关键词： hepatitis auxiliary diagnosis GA-BP neural network fuzzy integral

学校读者我要写书评

暂无评论

INTRODUCTION

Bulletin of the American Meteorological Society 2024年第8期105卷 S1-S11页

作者： Boyer, T. Blunden, J. Dunn, R.J.H. NOAA/NESDIS National Centers for Environmental Information Silver Spring Maryland NOAA/NESDIS National Centers for Environmental Information Asheville North Carolina Met Office Hadley Centre Exeter United Kingdom European Centre for Medium-Range Weather Forecasts Reading United Kingdom University of Maryland College Park Maryland Scripps Institution of Oceanography University of California San Diego La Jolla California NOAA/NWS National Centers for Environmental Prediction Climate Prediction Center College Park Maryland Brandenburg University of Technology (BTU) Cottbus-Senftenberg Germany Servicio Meteorológico Nacional Buenos Aires Argentina NOAA/OAR Physical Sciences Laboratory Boulder Colorado European Centre for Medium-Range Weather Forecasts Bonn Germany Center for Geophysical Research and School of Physics University of Costa Rica San José Costa Rica Department of Meteorology and National Centre for Earth Observation University of Reading Reading United Kingdom Centro Nacional de Monitoramento e Alertas de Desastres Naturais CEMADEN São Paulo Brazil Université Grenoble Alpes Institut des Géosciences de l’Environnement IRD CNRS Grenoble INP Grenoble France Hampton University Hampton Virginia Seychelles Meteorological Authority Mahe Seychelles Section for Glaciers Ice and Snow Norwegian Water Resources and Energy Directorate Oslo Norway National Research Institute for Agriculture Food and Environment (INRAE) CARRTEL Université Savoie Mont Blanc Thonon les Bains France Graduate School of Agriculture Osaka Metropolitan University Sakai Japan Science Faculty Universidad Nacional de Colombia Bogotá Colombia University of Bremen Bremen Germany NOAA Global Monitoring Laboratory Boulder Colorado Servicio Nacional de Meteorología e Hidrología del Perú Lima Perú Centro de Investigaciones sobre Desertificación – Spanish National Research Council (CSIC-UV-GVA) Valencia Spain Hydro-Climate Extremes Lab (H-CEL) Ghent University Ghent Belgium Department o

In 2023, La Niña conditions that generally prevailed in the eastern Pacific Ocean from mid-2020 into early 2023 gave way to a strong El Niño by October. Atmospheric concentrations of Earth’s major greenhouse gases—carbon dioxide, methane, and nitrous oxide—all increased to record-high levels. The annual global average carbon dioxide concentration in the atmosphere rose to 419.3±0.1 ppm, which is 50% greater than the pre-industrial level. The growth from 2022 to 2023 was 2.8 ppm, the fourth highest in the record since the 1960s. The combined short-term effects of El Niño and the long-term effects of increasing levels of heat-trapping gases in the atmosphere contributed to new records for many essential climate variables reported here. The annual global temperature across land and oceans was the highest in records dating as far back as 1850, with the last seven months (June–December) having each been record warm. Over land, the globally averaged temperature was also record high. Dozens of countries reported record or near-record warmth for the year, including China and continental Europe as a whole (warmest on record), India and Russia (second warmest), and Canada (third warmest). Intense and widespread heatwaves were reported around the world. In Vietnam, an all-time national maximum temperature record of 44.2°C was observed at Tuong Duong on 7 May, surpassing the previous record of 43.4°C at Huong Khe on 20 April 2019. In Brazil, the air temperature reached 44.8°C in Araçuaí in Minas Gerais on 20 November, potentially a new national record and 12.8°C above normal. The effect of rising temperatures was apparent in the cryosphere, where snow cover extent by June 2023 was the smallest in the 56-year record for North America and seventh smallest for the Northern Hemisphere overall. Heatwaves contributed to the greatest average mass balance loss for Alpine glaciers around the world since the start of the record in 1970. Due to rapid volume loss beginning in 2021, St. A

关键词：

Learning converged propagations with deep prior ensemble for image enhancement

学校读者我要写书评

暂无评论

arXiv 2018年

作者： Liu, Risheng Ma, Long Wang, Yiyang Zhang, Lei DUT-RU International School of Information Science & Engineering Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province Dalian University of Technology Dalian China State Key Laboratory of Integrated Services Networks Xidian University Xi'an China Institute of Atmospheric Sciences Fudan University Shanghai Institute of Meteorological Science Shanghai China Department of Computing Hong Kong Polytechnic University Hong Kong

Enhancing visual qualities of images plays very important roles in various vision and learning applications. In the past few years, both knowledge-driven maximum a posterior (MAP) with prior modelings and fully data-dependent convolutional neural network (CNN) techniques have been investigated to address specific enhancement tasks. In this paper, by exploiting the advantages of these two types of mechanisms within a complementary propagation perspective, we propose a unified framework, named deep prior ensemble (DPE), for solving various image enhancement tasks. Specifically, we first establish the basic propagation scheme based on the fundamental image modeling cues and then introduce residual CNNs to help predicting the propagation direction at each stage. By designing prior projections to perform feedback control, we theoretically prove that even with experience-inspired CNNs, DPE is definitely converged and the output will always satisfy our fundamental task constraints. The main advantage against conventional optimization-based MAP approaches is that our descent directions are learned from collected training data, thus are much more robust to unwanted local minimums. While, compared with existing CNN type networks, which are often designed in heuristic manners without theoretical guarantees, DPE is able to gain advantages from rich task cues investigated on the bases of domain knowledges. Therefore, DPE actually provides a generic ensemble methodology to integrate both knowledge and data-based cues for different image enhancement tasks. More importantly, our theoretical investigations verify that the feed-forward propagations of DPE are properly controlled toward our desired solution. Experimental results demonstrate that the proposed DPE outperforms state-of-the-arts on a variety of image enhancement tasks in terms of both quantitative measure and visual perception quality. Copyright © 2018, The Authors. All rights reserved.

关键词： Image enhancement

Automatic vector-based road structure mapping using multi-beam lidar

学校读者我要写书评

暂无评论

arXiv 2018年

作者： He, Xudong Zhao, Junqiao Sun, Lu Huang, Yewei Zhang, Xinglian Li, Jun Ye, Chen Key Laboratory of Embedded System and Service Computing Tongji University Ministry of Education Shanghai Department of Computer Science and Technology School of Electronics and Information Engineering Tongji University Shanghai School of Surveying and Geo-Informatics Tongji University Shanghai China School of Automotive Studies Tongji University Shanghai China

In this paper, we studied a SLAM method for vector-based road structure mapping using multi-beam LiDAR. We propose to use the polyline as the primary mapping element instead of grid cell or point cloud, because the vector-based representation is precise and lightweight, and it can directly generate vector-based High-Definition (HD) driving map as demanded by autonomous driving systems. We explored: 1) the extraction and vectorization of road structures based on local probabilistic fusion. 2) the efficient vector-based matching between frames of road structures. 3) the loop closure and optimization based on the pose-graph. In this study, we took a specific road structure, the road boundary, as an example. We applied the proposed matching method in three different scenes and achieved the average absolute matching error of 0.07 m. We further applied the mapping system to the urban road with the length of 860 meters and achieved an average global accuracy of 0.466 m without the help of high precision GPS. Copyright © 2018, The Authors. All rights reserved.

关键词： Mapping

TiEV: The tongji intelligent electric vehicle in the intelligent vehicle future challenge of China

学校读者我要写书评

暂无评论

arXiv 2018年

作者： Zhao, Junqiao Ye, Chen Wu, Yan Guan, Linting Cai, Lewen Sun, Lu Yang, Tao He, Xudong Li, Jun Ding, Yongchao Zhang, Xinglian Wang, Xinchen Huang, Jinlin Zhang, Enwei Huang, Yewei Jiang, Wei Zhang, Shaoming Xiong, Lu Feng, Tiantian Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai Department of Computer Science and Technology School of electrics and Information Engineering Tongji University Shanghai School of Surveying and Geo-Informatics Tongji University Shanghai China School of Automotive Studies Tongji University Shanghai China

TiEV is an autonomous driving platform implemented by the Tongji University of China. The vehicle is drive-by-wire and is fully powered by electricity. We devised the software system of TiEV from scratch, which is capable of driving the vehicle autonomously in urban paths as well as on fast express roads. We describe our whole system, especially novel modules of probabilistic perception fusion, large-scale mapping and updating, the 1st and the 2nd planning and the overall safety concern. TiEV finished 2016, and 2017 Intelligent Vehicle Future Challenge of China held at Changshu. We show our experiences on the development of autonomous vehicles and discuss the future trends. Copyright © 2018, The Authors. All rights reserved.

关键词： Autonomous vehicles

Design and Experimental Study of Tunable Fiber Ring Laser of C+L Band

学校读者我要写书评

暂无评论

Design and Experimental Study of Tunable Fiber Ring Laser of...

2017 2nd International Conference on Electrical and Electronics: Techniques and Applications（EETA2017）

作者： Dan WANG Yun-wei JIA Yan-bing XUE Chun-lei ZHAO Key Laboratory of Computer Vision and System Tianjin University of Technology Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin University of Technology School of Mechanical Engineering Tianjin University of Technology

A tunable fiber ring laser based on L band EDFA(erbium-doped fiber amplifier) was proposed. It has high signal-to-noise ratio and wide tuning range. The influence factor of the tuning range and the time delay of relaxation oscillation were studied. And the FFP-TF(Fabry-Perot tunable filter) was used as a wavelength selector to produce tunable laser. Experiments show that by using appropriate time-delay and auto-adjusting the intra-cavity loss, the signal-to-noise ratio can be increased and the tunable range can be broadened to C+L band.

关键词： Fiber laser Tunable filter Erbium-doped fiber Intra-cavity loss Laser sensing

A data acquisition system of CNC based on Zigbee and GPRS technology

学校读者我要写书评

暂无评论

A data acquisition system of CNC based on Zigbee and GPRS te...

2016 IEEE Advanced Information Management,Communicates,Electronic and Automation Control Conference(IMCEC 2016)

作者： Xiao Bin CAO Xiang Li ZHANG Hong Mei ZHANG Key Laboratory of Cloud Computing & Complex System Guilin University of Electronic Technology

ISBN: (纸本)9781509001668

A data acquisition and monitoring system of machine tools is designed,which is based on Zigbee and GPRS wireless communication *** monitoring and alerting about the safety status of the machine tools operates via the acquisition of such physical parameters as temperature and *** hardware such as the CC2530 RF circuit and power module is *** on the CC2530 module and SIM900 module,the wireless transmission and SMS alarm can be *** detailed design process of the software is also given in this paper,besides,the data monitoring is carried out on the PC software *** turns out to be a success of this security monitoring system which integrates the data acquisition and transmission of machine tool and alarm system under the industrial *** software platform overcomes the shortcomings such as the poor realtime performance of traditional CNC machine tools monitoring system and the difficulty of data transmission,and shows an extensive range of applicability.

关键词： CNC monitoring realtime performance Zigbee GPRS