Institution
University of Oxford
Education•Oxford, Oxfordshire, United Kingdom•
About: University of Oxford is a education organization based out in Oxford, Oxfordshire, United Kingdom. It is known for research contribution in the topics: Population & Galaxy. The organization has 99713 authors who have published 258108 publications receiving 12972806 citations. The organization is also known as: Oxford University & Oxon..
Papers published on a yearly basis
Papers
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TL;DR: The state-of-the-art in evaluated methods for both classification and detection are reviewed, whether the methods are statistically different, what they are learning from the images, and what the methods find easy or confuse.
Abstract: The Pascal Visual Object Classes (VOC) challenge is a benchmark in visual object category recognition and detection, providing the vision and machine learning communities with a standard dataset of images and annotation, and standard evaluation procedures. Organised annually from 2005 to present, the challenge and its associated dataset has become accepted as the benchmark for object detection.
This paper describes the dataset and evaluation procedure. We review the state-of-the-art in evaluated methods for both classification and detection, analyse whether the methods are statistically different, what they are learning from the images (e.g. the object or its context), and what the methods find easy or confuse. The paper concludes with lessons learnt in the three year history of the challenge, and proposes directions for future improvement and extension.
15,935 citations
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TL;DR: An instrument to assess the quality of reports of randomized clinical trials (RCTs) in pain research is described and its use to determine the effect of rater blinding on the assessments of quality is described.
15,740 citations
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01 Jan 2000TL;DR: In this article, the authors provide comprehensive background material and explain how to apply the methods and implement the algorithms directly in a unified framework, including geometric principles and how to represent objects algebraically so they can be computed and applied.
Abstract: From the Publisher:
A basic problem in computer vision is to understand the structure of a real world scene given several images of it. Recent major developments in the theory and practice of scene reconstruction are described in detail in a unified framework. The book covers the geometric principles and how to represent objects algebraically so they can be computed and applied. The authors provide comprehensive background material and explain how to apply the methods and implement the algorithms directly.
15,558 citations
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TL;DR: The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) initiative developed recommendations on what should be included in an accurate and complete report of an observational study, resulting in a checklist of 22 items (the STROBE statement) that relate to the title, abstract, introduction, methods, results, and discussion sections of articles.
Abstract: Much biomedical research is observational. The reporting of such research is often inadequate, which hampers the assessment of its strengths and weaknesses and of a study's generalisability. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Initiative developed recommendations on what should be included in an accurate and complete report of an observational study. We defined the scope of the recommendations to cover three main study designs: cohort, case-control, and cross-sectional studies. We convened a 2-day workshop in September 2004, with methodologists, researchers, and journal editors to draft a checklist of items. This list was subsequently revised during several meetings of the coordinating group and in e-mail discussions with the larger group of STROBE contributors, taking into account empirical evidence and methodological considerations. The workshop and the subsequent iterative process of consultation and revision resulted in a checklist of 22 items (the STROBE Statement) that relate to the title, abstract, introduction, methods, results, and discussion sections of articles. 18 items are common to all three study designs and four are specific for cohort, case-control, or cross-sectional studies. A detailed Explanation and Elaboration document is published separately and is freely available on the Web sites of PLoS Medicine, Annals of Internal Medicine, and Epidemiology. We hope that the STROBE Statement will contribute to improving the quality of reporting of observational studies.
15,454 citations
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TL;DR: In this article, the authors present a model that incorporates this overall argument in the form of a series of hypothesized relationships between different dimensions of social capital and the main mechanisms and proces.
Abstract: Scholars of the theory of the firm have begun to emphasize the sources and conditions of what has been described as “the organizational advantage,” rather than focus on the causes and consequences of market failure. Typically, researchers see such organizational advantage as accruing from the particular capabilities organizations have for creating and sharing knowledge. In this article we seek to contribute to this body of work by developing the following arguments: (1) social capital facilitates the creation of new intellectual capital; (2) organizations, as institutional settings, are conducive to the development of high levels of social capital; and (3) it is because of their more dense social capital that firms, within certain limits, have an advantage over markets in creating and sharing intellectual capital. We present a model that incorporates this overall argument in the form of a series of hypothesized relationships between different dimensions of social capital and the main mechanisms and proces...
15,365 citations
Authors
Showing all 101421 results
Name | H-index | Papers | Citations |
---|---|---|---|
Eric S. Lander | 301 | 826 | 525976 |
Albert Hofman | 267 | 2530 | 321405 |
Douglas G. Altman | 253 | 1001 | 680344 |
Salim Yusuf | 231 | 1439 | 252912 |
George Davey Smith | 224 | 2540 | 248373 |
Yi Chen | 217 | 4342 | 293080 |
David J. Hunter | 213 | 1836 | 207050 |
Nicholas J. Wareham | 212 | 1657 | 204896 |
Christopher J L Murray | 209 | 754 | 310329 |
Cyrus Cooper | 204 | 1869 | 206782 |
Mark J. Daly | 204 | 763 | 304452 |
David Miller | 203 | 2573 | 204840 |
Mark I. McCarthy | 200 | 1028 | 187898 |
Raymond J. Dolan | 196 | 919 | 138540 |
Frank E. Speizer | 193 | 636 | 135891 |