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Institution

University of Cambridge

EducationCambridge, United Kingdom
About: University of Cambridge is a(n) education organization based out in Cambridge, United Kingdom. It is known for research contribution in the topic(s): Population & Galaxy. The organization has 118293 authors who have published 282289 publication(s) receiving 14497093 citation(s). The organization is also known as: Cambridge University & Cambridge.
Topics: Population, Galaxy, Transplantation, Redshift, Gene
Papers
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Journal ArticleDOI
TL;DR: Quantitative assessments show that SegNet provides good performance with competitive inference time and most efficient inference memory-wise as compared to other architectures, including FCN and DeconvNet.
Abstract: We present a novel and practical deep fully convolutional neural network architecture for semantic pixel-wise segmentation termed SegNet. This core trainable segmentation engine consists of an encoder network, a corresponding decoder network followed by a pixel-wise classification layer. The architecture of the encoder network is topologically identical to the 13 convolutional layers in the VGG16 network [1] . The role of the decoder network is to map the low resolution encoder feature maps to full input resolution feature maps for pixel-wise classification. The novelty of SegNet lies is in the manner in which the decoder upsamples its lower resolution input feature map(s). Specifically, the decoder uses pooling indices computed in the max-pooling step of the corresponding encoder to perform non-linear upsampling. This eliminates the need for learning to upsample. The upsampled maps are sparse and are then convolved with trainable filters to produce dense feature maps. We compare our proposed architecture with the widely adopted FCN [2] and also with the well known DeepLab-LargeFOV [3] , DeconvNet [4] architectures. This comparison reveals the memory versus accuracy trade-off involved in achieving good segmentation performance. SegNet was primarily motivated by scene understanding applications. Hence, it is designed to be efficient both in terms of memory and computational time during inference. It is also significantly smaller in the number of trainable parameters than other competing architectures and can be trained end-to-end using stochastic gradient descent. We also performed a controlled benchmark of SegNet and other architectures on both road scenes and SUN RGB-D indoor scene segmentation tasks. These quantitative assessments show that SegNet provides good performance with competitive inference time and most efficient inference memory-wise as compared to other architectures. We also provide a Caffe implementation of SegNet and a web demo at http://mi.eng.cam.ac.uk/projects/segnet/ .

8,450 citations


Journal ArticleDOI
TL;DR: This article reviews studies investigating complex brain networks in diverse experimental modalities and provides an accessible introduction to the basic principles of graph theory and highlights the technical challenges and key questions to be addressed by future developments in this rapidly moving field.
Abstract: Recent developments in the quantitative analysis of complex networks, based largely on graph theory, have been rapidly translated to studies of brain network organization. The brain's structural and functional systems have features of complex networks--such as small-world topology, highly connected hubs and modularity--both at the whole-brain scale of human neuroimaging and at a cellular scale in non-human animals. In this article, we review studies investigating complex brain networks in diverse experimental modalities (including structural and functional MRI, diffusion tensor imaging, magnetoencephalography and electroencephalography in humans) and provide an accessible introduction to the basic principles of graph theory. We also highlight some of the technical challenges and key questions to be addressed by future developments in this rapidly moving field.

8,306 citations


Journal ArticleDOI
Stephen S Lim1, Theo Vos, Abraham D. Flaxman1, Goodarz Danaei2, Kenji Shibuya, Heather Adair-Rohani3, Mohammad A. AlMazroa, Markus Amann4, H. Ross Anderson5, Kathryn G. Andrews1, Martin J. Aryee, Charles Atkinson1, Loraine J. Bacchus6, Adil N. Bahalim, Kalpana Balakrishnan7, John R. Balmes, Suzanne Barker-Collo8, Amanda J Baxter9, Michelle L. Bell10, Jed D. Blore, Fiona M. Blyth11, Carissa Bonner11, Guilherme Borges12, Rupert R A Bourne13, Michel Boussinesq14, Michael Brauer15, Peter Brooks16, Nigel Bruce17, Bert Brunekreef18, Claire Bryan-Hancock19, Chiara Bucello20, Rachelle Buchbinder21, Fiona Bull22, Richard T. Burnett23, Tim Byers24, Bianca Calabria25, Jonathan R. Carapetis26, Emily Carnahan1, Zoë Chafe3, Fiona J Charlson, Honglei Chen27, Jian Shen Chen, Andrew T. A. Cheng28, Jennifer C. Child6, Aaron Cohen29, K. Ellicott Colson1, Benjamin C Cowie16, Sarah C. Darby30, Susan Darling11, Adrian Davis, Louisa Degenhardt25, Frank Dentener, Don C. Des Jarlais31, Karen Devries6, Mukesh Dherani17, Eric L. Ding2, E. Ray Dorsey32, Tim Driscoll, Karen Edmond6, S. Ali, Rebecca E. Engell1, Patricia J. Erwin33, Saman Fahimi34, Gail Falder6, Farshad Farzadfar35, Alize J. Ferrari9, Mariel M. Finucane2, Seth Flaxman36, F.G.R. Fowkes37, Greg Freedman1, Michael Freeman1, Emmanuela Gakidou1, Santu Ghosh7, Edward Giovannucci2, Gerhard Gmel, Kathryn Graham38, Rebecca Grainger39, Rebecca Grainger27, Bridget F. Grant27, David Gunnell40, Hialy R. Gutierrez41, Wayne Hall42, Hans W. Hoek, Anthony Hogan43, H. Dean Hosgood44, Damian G Hoy21, Howard Hu45, Bryan Hubbell46, Sally Hutchings47, Sydney E. Ibeanusi48, Gemma Jacklyn11, Rashmi Jasrasaria1, Jost B. Jonas49, Haidong Kan50, John A. Kanis51, Nicholas J Kassebaum, Norito Kawakami52, Young-Ho Khang53, Shahab Khatibzadeh2, Jon-Paul Khoo9, Cindy Kok, Francine Laden2, Ratilal Lalloo, Qing Lan, Tim Lathlean19, Janet L Leasher54, James Leigh, Yang Li, John K Lin2, Steven E. Lipshultz55, Stephanie J. London27, Rafael Lozano1, Yuan Lu2, Joelle Mak6, Reza Malekzadeh, Leslie Mallinger1, Wagner Marcenes56, Lyn March, Robin Marks16, Randall V. Martin57, Paul McGale, John J. McGrath58, Sumi Mehta, Ziad A. Memish59, George A. Mensah60, Tony R. Merriman39, Renata Micha2, Renata Micha61, Catherine Michaud62, Vinod Mishra63, Khayriyyah Mohd Hanafiah32, Ali A. Mokdad1, Lidia Morawska, Dariush Mozaffarian2, Tasha B. Murphy1, Mohsen Naghavi1, Bruce Neal64, Paul K. Nelson25, Joan M. Nolla, Rosana E. Norman, Casey Olives65, Saad B. Omer66, Jessica Orchard11, Richard H. Osborne67, Bart Ostro68, Andrew Page, Kiran Pandey69, Charles D. H. Parry70, Erin Passmore11, Jayadeep Patra, Neil Pearce6, Pamela M. Pelizzari71, Max Petzold72, Michael Phillips73, Daniel Pope17, C. Arden Pope74, John Powles34, Mayuree Rao2, Homie Razavi, Eva Rehfuess75, Jürgen Rehm38, Beate Ritz76, Frederick P. Rivara65, Thomas Roberts1, Carolyn Robinson77, Jose Adolfo Rodriguez-Portales78, Isabelle Romieu79, Robin Room80, Lisa C. Rosenfeld1, Ananya Roy81, Lesley Rushton47, Joshua A. Salomon2, Uchechukwu Sampson82, Lidia Sanchez-Riera, Ella Sanman1, Amir Sapkota83, Soraya Seedat84, Peilin Shi2, Kevin D. Shield38, Rupak Shivakoti32, Gitanjali M Singh2, David A. Sleet, Emma Smith, Kirk R. Smith3, Nicolas J. C. Stapelberg85, Kyle Steenland66, Heidi Stöckl6, Lars Jacob Stovner86, Kurt Straif79, Lahn Straney1, George D. Thurston87, Jimmy H. Tran3, Rita Van Dingenen, Aaron van Donkelaar57, J. Lennert Veerman42, Lakshmi Vijayakumar, Robert G. Weintraub88, Myrna M. Weissman41, Richard A. White2, Harvey Whiteford9, Steven T. Wiersma89, James D. Wilkinson55, Hywel C Williams90, Warwick Williams, Nick Wilson, Anthony D. Woolf91, Paul S. F. Yip92, Jan M Zielinski23, Alan D. Lopez, Christopher J L Murray1, Majid Ezzati47 
Institute for Health Metrics and Evaluation1, Harvard University2, University of California, Berkeley3, International Institute for Applied Systems Analysis4, St George's, University of London5, University of London6, Sri Ramachandra University7, University of Auckland8, Centre for Mental Health9, Yale University10, University of Sydney11, Universidad Autónoma Metropolitana12, Anglia Ruskin University13, Institut de recherche pour le développement14, University of British Columbia15, University of Melbourne16, University of Liverpool17, Utrecht University18, Flinders University19, University of New South Wales20, Monash University21, University of Western Australia22, Health Canada23, Colorado School of Public Health24, National Drug and Alcohol Research Centre25, Telethon Institute for Child Health Research26, National Institutes of Health27, Academia Sinica28, Health Effects Institute29, University of Oxford30, Beth Israel Medical Center31, Johns Hopkins University32, Mayo Clinic33, University of Cambridge34, Tehran University of Medical Sciences35, Carnegie Mellon University36, University of Edinburgh37, Centre for Addiction and Mental Health38, University of Otago39, University of Bristol40, Columbia University41, University of Queensland42, Australian National University43, Albert Einstein College of Medicine44, University of Toronto45, United States Environmental Protection Agency46, Imperial College London47, University of Port Harcourt48, Heidelberg University49, Fudan University50, University of Sheffield51, University of Tokyo52, University of Ulsan53, Nova Southeastern University54, University of Miami55, Queen Mary University of London56, Dalhousie University57, Allen Institute for Brain Science58, Alfaisal University59, University of Cape Town60, Agricultural University of Athens61, China Medical Board62, United Nations63, The George Institute for Global Health64, University of Washington65, Emory University66, Deakin University67, California Environmental Protection Agency68, World Bank69, South African Medical Research Council70, Centers for Medicare and Medicaid Services71, University of Gothenburg72, Shanghai Jiao Tong University73, Brigham Young University74, Ludwig Maximilian University of Munich75, University of California, Los Angeles76, University of California, San Francisco77, Pontifical Catholic University of Chile78, International Agency for Research on Cancer79, Turning Point Alcohol and Drug Centre80, University of Medicine and Dentistry of New Jersey81, Vanderbilt University82, University of Maryland, Baltimore83, Stellenbosch University84, Griffith University85, Norwegian University of Science and Technology86, New York University87, Royal Children's Hospital88, Centers for Disease Control and Prevention89, University of Nottingham90, Royal Cornwall Hospital91, University of Hong Kong92
15 Dec 2012-The Lancet
Abstract: Methods We estimated deaths and disability-adjusted life years (DALYs; sum of years lived with disability [YLD] and years of life lost [YLL]) attributable to the independent eff ects of 67 risk factors and clusters of risk factors for 21 regions in 1990 and 2010. W e estimated exposure distributions for each year, region, sex, and age group, and relative risks per unit of exposure by systematically reviewing and synthesising published and unpublished data. We used these estimates, together with estimates of cause-specifi c deaths and DALYs from the Global Burden of Disease Study 2010, to calculate the burden attributable to each risk factor exposure compared with the theoretical-minimum-risk exposure. We incorporated uncertainty in disease burden, relative risks, and exposures into our estimates of attributable burden. Findings In 2010, the three leading risk factors for global disease burden were high blood pressure (7·0% [95% uncertainty interval 6·2–7·7] of global DALYs), tobacco smoking including second-hand smoke (6·3% [5·5–7·0]), and alcohol use (5·5% [5·0–5·9]). In 1990, the leading risks were childhood underweight (7·9% [6·8–9·4]), household air pollution from solid fuels (HAP; 7·0% [5·6–8·3]), and tobacco smoking including second-hand smoke (6·1% [5·4–6·8]). Dietary risk factors and physical inactivity collectively accounted for 10·0% (95% UI 9·2–10·8) of global DALYs in 2010, with the most prominent dietary risks being diets low in fruits and those high in sodium. Several risks that primarily aff ect childhood communicable diseases, including unimproved water and sanitation and childhood micronutrient defi ciencies, fell in rank between 1990 and 2010, with unimproved water

8,301 citations


8


Journal ArticleDOI
TL;DR: The basics of the suject are looked at, a brief review of the theory is given, examining the strengths and weaknesses of its implementation, and some of the ways simulators approach problems are illustrated through a small case study.
Abstract: First-principles simulation, meaning density-functional theory calculations with plane waves and pseudopotentials, has become a prized technique in condensed-matter theory. Here I look at the basics of the suject, give a brief review of the theory, examining the strengths and weaknesses of its implementation, and illustrating some of the ways simulators approach problems through a small case study. I also discuss why and how modern software design methods have been used in writing a completely new modular version of the CASTEP code.

8,251 citations


Book
01 Jan 1965-
TL;DR: Algebra of Vectors and Matrices, Probability Theory, Tools and Techniques, and Continuous Probability Models.
Abstract: Algebra of Vectors and Matrices. Probability Theory, Tools and Techniques. Continuous Probability Models. The Theory of Least Squares and Analysis of Variance. Criteria and Methods of Estimation. Large Sample Theory and Methods. Theory of Statistical Inference. Multivariate Analysis. Publications of the Author. Author Index. Subject Index.

8,165 citations


Authors

Showing all 118293 results

NameH-indexPapersCitations
Albert Hofman2672530321405
Zhong Lin Wang2452529259003
Solomon H. Snyder2321222200444
Trevor W. Robbins2311137164437
George Davey Smith2242540248373
Nicholas J. Wareham2121657204896
Cyrus Cooper2041869206782
Eric B. Rimm196988147119
Martin White1962038232387
Simon D. M. White189795231645
Michael Rutter188676151592
George Efstathiou187637156228
Mark Hallett1861170123741
David H. Weinberg183700171424
Paul G. Richardson1831533155912
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2022186
202115,670
202015,347
201913,661
201812,548
201712,444

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Institution's top 5 most impactful journals

Nature

4.7K papers, 693.3K citations

bioRxiv

3.6K papers, 17K citations

Social Science Research Network

3.2K papers, 75.5K citations

The Astrophysical Journal

1.9K papers, 244.2K citations