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Eric A. Lehmann
Researcher at Commonwealth Scientific and Industrial Research Organisation
Publications - 43
Citations - 1721
Eric A. Lehmann is an academic researcher from Commonwealth Scientific and Industrial Research Organisation. The author has contributed to research in topics: Particle filter & Land cover. The author has an hindex of 16, co-authored 43 publications receiving 1524 citations. Previous affiliations of Eric A. Lehmann include University of Stirling & Australian National University.
Papers
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Journal ArticleDOI
Particle filtering algorithms for tracking an acoustic source in a reverberant environment
TL;DR: A general framework for tracking an acoustic source using particle filters is formulated and four specific algorithms that fit within this framework are discussed, and results indicate that the proposed family of algorithms are able to accurately track a moving source in a moderately reverberant room.
Journal ArticleDOI
Prediction of energy decay in room impulse responses simulated with an image-source model
TL;DR: The technique presented in this work enables designers to undertake a preliminary analysis of a simulated reverberant environment without the need for time-consuming image-method simulations.
Journal ArticleDOI
Diffuse Reverberation Model for Efficient Image-Source Simulation of Room Impulse Responses
Eric A. Lehmann,A M Johansson +1 more
TL;DR: The diffuse reverberation model presented in this paper produces impulse responses that are representative of the specific virtual environment under consideration (within the general assumptions of geometrical room acoustics), in contrast to other artificial reverberation techniques developed on the basis of perceptual measures or assuming a purely exponential energy decay.
Journal ArticleDOI
Combining satellite data for better tropical forest monitoring
Johannes Reiche,Richard Lucas,Anthea Mitchell,Jan Verbesselt,Dirk Hoekman,Jörg Haarpaintner,Josef Kellndorfer,Ake Rosenqvist,Eric A. Lehmann,Curtis E. Woodcock,Frank Martin Seifert,Martin Herold +11 more
TL;DR: In this paper, the use of new satellite missions and the combining of optical and synthetic aperture radar sensor data is proposed to reduce forest loss in Earth observation community to improve forest monitoring.
Journal ArticleDOI
Forest cover trends from time series Landsat data for the Australian continent
TL;DR: The operational methods used for the generation of National Forest Trend information is described, which is a time-series summary providing visual indication of within-forest vegetation changes (disturbance and recovery) over time at 25 m resolution, based on a national archive of calibrated Landsat TM/ETM+.