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Institution

University of Adelaide

EducationAdelaide, South Australia, Australia
About: University of Adelaide is a education organization based out in Adelaide, South Australia, Australia. It is known for research contribution in the topics: Population & Poison control. The organization has 27251 authors who have published 79167 publications receiving 2671128 citations. The organization is also known as: The University of Adelaide & Adelaide University.


Papers
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Journal ArticleDOI
TL;DR: The largest declines in risk exposure from 2010 to 2019 were among a set of risks that are strongly linked to social and economic development, including household air pollution; unsafe water, sanitation, and handwashing; and child growth failure.

3,059 citations

Journal ArticleDOI
TL;DR: In this paper, the contribution of cosmic rays to the dose rates for TL/ESR dating depends on altitude, latitude and depth below ground level, and the effects are shown to be small over the past 500 ka in most circumstances.

3,042 citations

Journal ArticleDOI
Jeffrey D. Stanaway1, Ashkan Afshin1, Emmanuela Gakidou1, Stephen S Lim1  +1050 moreInstitutions (346)
TL;DR: This study estimated levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs) by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or groups of risks from 1990 to 2017 and explored the relationship between development and risk exposure.

2,910 citations

Proceedings ArticleDOI
18 Jun 2018
TL;DR: In this paper, a bottom-up and top-down attention mechanism was proposed to enable attention to be calculated at the level of objects and other salient image regions, which achieved state-of-the-art results on the MSCOCO test server.
Abstract: Top-down visual attention mechanisms have been used extensively in image captioning and visual question answering (VQA) to enable deeper image understanding through fine-grained analysis and even multiple steps of reasoning. In this work, we propose a combined bottom-up and top-down attention mechanism that enables attention to be calculated at the level of objects and other salient image regions. This is the natural basis for attention to be considered. Within our approach, the bottom-up mechanism (based on Faster R-CNN) proposes image regions, each with an associated feature vector, while the top-down mechanism determines feature weightings. Applying this approach to image captioning, our results on the MSCOCO test server establish a new state-of-the-art for the task, achieving CIDEr / SPICE / BLEU-4 scores of 117.9, 21.5 and 36.9, respectively. Demonstrating the broad applicability of the method, applying the same approach to VQA we obtain first place in the 2017 VQA Challenge.

2,904 citations


Authors

Showing all 27579 results

NameH-indexPapersCitations
Martin White1962038232387
Nicholas G. Martin1921770161952
David W. Johnson1602714140778
Nicholas J. Talley158157190197
Mark E. Cooper1581463124887
Xiang Zhang1541733117576
John E. Morley154137797021
Howard I. Scher151944101737
Christopher M. Dobson1501008105475
A. Artamonov1501858119791
Timothy P. Hughes14583191357
Christopher Hill1441562128098
Shi-Zhang Qiao14252380888
Paul Jackson141137293464
H. A. Neal1411903115480
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023127
2022597
20215,500
20205,342
20194,803
20184,443