Institution
Commonwealth Scientific and Industrial Research Organisation
Government•Canberra, Australian Capital Territory, Australia•
About: Commonwealth Scientific and Industrial Research Organisation is a government organization based out in Canberra, Australian Capital Territory, Australia. It is known for research contribution in the topics: Population & Soil water. The organization has 33765 authors who have published 79910 publications receiving 3356114 citations.
Topics: Population, Soil water, Climate change, Gene, Context (language use)
Papers published on a yearly basis
Papers
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Smithsonian Tropical Research Institute1, James Cook University2, Duke University3, University of Florida4, Louisiana State University5, National Autonomous University of Mexico6, National Marine Fisheries Service7, Rhodes College8, University of Western Australia9, Commonwealth Scientific and Industrial Research Organisation10, George Mason University11
TL;DR: In this paper, the authors synthesize findings to date from the world's largest and longest-running experimental study of habitat fragmentation, located in central Amazonia, and synthesize the results to date.
745 citations
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University of Ljubljana1, University of Birmingham2, Czech Technical University in Prague3, Linköping University4, Austrian Institute of Technology5, Carnegie Mellon University6, Parthenope University of Naples7, University of Isfahan8, Autonomous University of Madrid9, University of Ottawa10, University of Oxford11, Hong Kong Baptist University12, Kyiv Polytechnic Institute13, Middle East Technical University14, Hacettepe University15, King Abdullah University of Science and Technology16, Pohang University of Science and Technology17, University of Nottingham18, University at Albany, SUNY19, Chinese Academy of Sciences20, Dalian University of Technology21, Xi'an Jiaotong University22, Indian Institute of Space Science and Technology23, Hong Kong University of Science and Technology24, ASELSAN25, Commonwealth Scientific and Industrial Research Organisation26, Australian National University27, University of Missouri28, University of Verona29, Universidade Federal de Itajubá30, United States Naval Research Laboratory31, Marquette University32, Graz University of Technology33, Naver Corporation34, Imperial College London35, Electronics and Telecommunications Research Institute36, Zhejiang University37, University of Surrey38, Harbin Institute of Technology39, Lehigh University40
TL;DR: The Visual Object Tracking challenge VOT2016 goes beyond its predecessors by introducing a new semi-automatic ground truth bounding box annotation methodology and extending the evaluation system with the no-reset experiment.
Abstract: The Visual Object Tracking challenge VOT2016 aims at comparing short-term single-object visual trackers that do not apply pre-learned models of object appearance. Results of 70 trackers are presented, with a large number of trackers being published at major computer vision conferences and journals in the recent years. The number of tested state-of-the-art trackers makes the VOT 2016 the largest and most challenging benchmark on short-term tracking to date. For each participating tracker, a short description is provided in the Appendix. The VOT2016 goes beyond its predecessors by (i) introducing a new semi-automatic ground truth bounding box annotation methodology and (ii) extending the evaluation system with the no-reset experiment. The dataset, the evaluation kit as well as the results are publicly available at the challenge website (http://votchallenge.net).
744 citations
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TL;DR: A new procedure (DOMAIN) is described which computes potential distributions based on a range-standardized, point-to-point similarity metric and provides a simple, robust method for modelling potential distributions of plant and animal species.
Abstract: This paper briefly reviews some limitations associated with the application of existing modelling procedures to conservation ecology, and describes a new procedure (DOMAIN) which avoids these problems. The procedure computes potential distributions based on a range-standardized, point-to-point similarity metric and provides a simple, robust method for modelling potential distributions of plant and animal species. DOMAIN offers advantages over similar methods in its ability to operate effectively using only presence records and a limited number of biophysical attributes. The use of a continuous similarity function gives DOMAIN increased flexibility as an heuristic tool, suitable for application in survey design, reserve selection and potential mapping of rare and common species. Potential distributions were computed for two Australian marsupial bettong species (Aepyprymnus rufescens ‘Gray’ and Bettongia tropica Wakefield) using DOMAIN and two alternative models. Of the three procedures, the DOMAIN model produced distribution patterns that were most consistent with the known ecology of the species, and most appropriate for survey design.
741 citations
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12 Apr 2010
TL;DR: Ear-Phone, for the first time, leverages Compressive Sensing to address the fundamental problem of recovering the noise map from incomplete and random samples obtained by crowdsourcing data collection.
Abstract: A noise map facilitates monitoring of environmental noise pollution in urban areas. It can raise citizen awareness of noise pollution levels, and aid in the development of mitigation strategies to cope with the adverse effects. However, state-of-the-art techniques for rendering noise maps in urban areas are expensive and rarely updated (months or even years), as they rely on population and traffic models rather than on real data. Participatory urban sensing can be leveraged to create an open and inexpensive platform for rendering up-to-date noise maps.In this paper, we present the design, implementation and performance evaluation of an end-to-end participatory urban noise mapping system called Ear-Phone. Ear-Phone, for the first time, leverages Compressive Sensing to address the fundamental problem of recovering the noise map from incomplete and random samples obtained by crowdsourcing data collection. Ear-Phone, implemented on Nokia N95 and HP iPAQ mobile devices, also addresses the challenge of collecting accurate noise pollution readings at a mobile device. Extensive simulations and outdoor experiments demonstrate that Ear-Phone is a feasible platform to assess noise pollution, incurring reasonable system resource consumption at mobile devices and providing high reconstruction accuracy of the noise map.
741 citations
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National Center for Atmospheric Research1, Purdue University2, National Oceanic and Atmospheric Administration3, Tohoku University4, National Institute for Environmental Studies5, Nagoya University6, University of Leeds7, Max Planck Society8, Sukachev Institute of Forest9, Commonwealth Scientific and Industrial Research Organisation10, Colorado State University11
TL;DR: Measurements of midday vertical atmospheric CO2 distributions reveal annual-mean vertical CO2 gradients that are inconsistent with atmospheric models that estimate a large transfer of terrestrial carbon from tropical to northern latitudes, suggesting that northern terrestrial uptake of industrial CO2 emissions plays a smaller role than previously thought.
Abstract: Measurements of midday vertical atmospheric CO2 distributions reveal annual-mean vertical CO2 gradients that are inconsistent with atmospheric models that estimate a large transfer of terrestrial carbon from tropical to northern latitudes. The three models that most closely reproduce the observed annual-mean vertical CO2 gradients estimate weaker northern uptake of –1.5 petagrams of carbon per year (Pg C year–1) and weaker tropical emission of +0.1 Pg C year–1 compared with previous consensus estimates of –2.4 and +1.8 Pg C year–1, respectively. This suggests that northern terrestrial uptake of industrial CO2 emissions plays a smaller role than previously thought and that, after subtracting land-use emissions, tropical ecosystems may currently be strong sinks for CO2.
732 citations
Authors
Showing all 33864 results
Name | H-index | Papers | Citations |
---|---|---|---|
David R. Williams | 178 | 2034 | 138789 |
Mark E. Cooper | 158 | 1463 | 124887 |
Kevin J. Gaston | 150 | 750 | 85635 |
Liming Dai | 141 | 781 | 82937 |
John D. Potter | 137 | 795 | 75310 |
Lei Zhang | 135 | 2240 | 99365 |
Harold A. Mooney | 135 | 450 | 100404 |
Frederick M. Ausubel | 133 | 389 | 60365 |
Rajkumar Buyya | 133 | 1066 | 95164 |
Robert B. Jackson | 132 | 458 | 91332 |
Peter Hall | 132 | 1640 | 85019 |
Frank Caruso | 131 | 641 | 61748 |
Paul J. Crutzen | 130 | 461 | 80651 |
Andrew Y. Ng | 130 | 345 | 164995 |
Lei Zhang | 130 | 2312 | 86950 |