Added depth: automated high level image interpretation. Humans are very good at understanding the world through imagery, but computers lack this fundamental capacity because they lack experience of what they might see. This project will provide this experience by combining the large volumes of imagery on the Internet with three dimensional information generated by humans for other purposes.
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE130100156
Funder
Australian Research Council
Funding Amount
$210,000.00
Summary
Computational infrastructure for machine learning in computer vision. The many trillions of images stored on computers around the world, including more than 100 billion on Facebook alone, represent exactly the information needed to develop artificial vision. All we need do is extract it. This project will develop the computational infrastructure required to allow Australian researchers to achieve this goal.
Space-based space surveillance with robust computer vision algorithms. Space-based space surveillance with robust computer vision algorithms. This project aims to develop computer vision algorithms to detect man-made objects in space. These algorithms function on nanosatellite platforms, enabling space-based space surveillance. This technology is expected to provide always-on monitoring of the Earth's orbit to enhance existing defence infrastructure and protect vital space assets, including comm ....Space-based space surveillance with robust computer vision algorithms. Space-based space surveillance with robust computer vision algorithms. This project aims to develop computer vision algorithms to detect man-made objects in space. These algorithms function on nanosatellite platforms, enabling space-based space surveillance. This technology is expected to provide always-on monitoring of the Earth's orbit to enhance existing defence infrastructure and protect vital space assets, including communications and navigational satellites, in Earth’s orbit from collisions and covert sabotage. Increased space use by government and civilian agencies opens up opportunities for the space industry. This project is expected to develop Australia’s space surveillance capabilities, protect space assets and capture a growing market.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE160100090
Funder
Australian Research Council
Funding Amount
$250,000.00
Summary
Computational infrastructure for developing deep machine learning models. Computational infrastructure for developing deep machine learning models:
The computational infrastructure for developing deep machine learning models aims to enable new developments in machine learning of deep neural network models by providing the specialised computing necessary to train and evaluate the networks. In the last three years, deep networks have smashed previous performance ceilings for tasks such as object ....Computational infrastructure for developing deep machine learning models. Computational infrastructure for developing deep machine learning models:
The computational infrastructure for developing deep machine learning models aims to enable new developments in machine learning of deep neural network models by providing the specialised computing necessary to train and evaluate the networks. In the last three years, deep networks have smashed previous performance ceilings for tasks such as object recognition in images, speech recognition and automatic translation, bringing the prospect of machine intelligence closer than ever. Modern machine learning techniques have had huge impact in the last decade in fields such as robotics, computer vision and data analytics. The facility would enable Australian researchers to develop, learn and apply deep networks to problems of national importance in robotic vision and big data analytics. Read moreRead less
ARC Centre of Excellence for Robotic Vision. Robots are vital to Australia's future prosperity in the face of high relative wages, low or decreasing productivity, and impending labour shortages. However the work and workplaces of our most important industries are unstructured and changeable and current robots are challenged by their inability to quickly, safely and reliably "see" and "understand" what is around them. The Centre's research will create the fundamental science and technologies th ....ARC Centre of Excellence for Robotic Vision. Robots are vital to Australia's future prosperity in the face of high relative wages, low or decreasing productivity, and impending labour shortages. However the work and workplaces of our most important industries are unstructured and changeable and current robots are challenged by their inability to quickly, safely and reliably "see" and "understand" what is around them. The Centre's research will create the fundamental science and technologies that will allow robots to see as we do, and overcome the last barrier to the ubiquitous deployment of robots into society for the benefit of all.Read moreRead less
Applying search theory for eradicating invasive species. Invasive species have major economic and environmental impacts in Australia and are a major cause of extinctions worldwide. Monitoring is crucial for the timely control of invasive species in sensitive environments. Early detection increases the probability of eradication and increased accuracy in detection reduces the impact of control programs on non-target species. Efficient monitoring also is crucial in determining whether eradication ....Applying search theory for eradicating invasive species. Invasive species have major economic and environmental impacts in Australia and are a major cause of extinctions worldwide. Monitoring is crucial for the timely control of invasive species in sensitive environments. Early detection increases the probability of eradication and increased accuracy in detection reduces the impact of control programs on non-target species. Efficient monitoring also is crucial in determining whether eradication has succeeded. Search Theory has been applied for over 60 years in a wide range of non-biological monitoring problems, resulting in large increases in target detection rates. Gains of a similar magnitude in invasive species detection would greatly enhance Australia's capacity to manage these threats.Read moreRead less
Polymer nanoparticles and their assembled supracolloidal monolithic structures for applications in separation science. This project will generate new polymeric materials that will improve the analysis of complex samples. This will be applied in a wide range of areas of national importance including: pharmaceutical analysis and drug discovery; environmental, clinical and forensic analysis; and energy generation and foods.
Spatial-dynamic models to identify optimal fire mosaics, based on demography, dispersal and fire responses of plants, birds and reptiles. Inappropriate fire regimes threaten native species with extinction. The threat is higher in cleared landscapes where habitat is isolated and recolonisation unlikely. Furthermore, climate change is predicted to increase the frequency of intense bushfires. To meet the priority goals Sustainable Use of Biodiversity, and Responding to Climate Change, landscape-sca ....Spatial-dynamic models to identify optimal fire mosaics, based on demography, dispersal and fire responses of plants, birds and reptiles. Inappropriate fire regimes threaten native species with extinction. The threat is higher in cleared landscapes where habitat is isolated and recolonisation unlikely. Furthermore, climate change is predicted to increase the frequency of intense bushfires. To meet the priority goals Sustainable Use of Biodiversity, and Responding to Climate Change, landscape-scale fire management is essential. We will use simulation models based on detailed biological data and fire-behaviour to explore large-scale and long-term consequences of alternate fire management policies. Our project will enable fire mosaics to be implemented that maintain biodiversity and will identify effective fire management responses to climate change, and habitat fragmentation.Read moreRead less
Modelling and control of mosquito-borne diseases in Darwin using long-term monitoring. Management of mosquito populations is a high public health priority because these insects can spread diseases such as malaria, dengue, Ross River virus, Barmah Forest virus, Murray Valley encephalitis, Japanese encephalitis and Kunjin/West Nile virus. Our research into the effectiveness of mosquito control programs in Darwin is of immediate national relevance and priority given the need to Safeguard Australia ....Modelling and control of mosquito-borne diseases in Darwin using long-term monitoring. Management of mosquito populations is a high public health priority because these insects can spread diseases such as malaria, dengue, Ross River virus, Barmah Forest virus, Murray Valley encephalitis, Japanese encephalitis and Kunjin/West Nile virus. Our research into the effectiveness of mosquito control programs in Darwin is of immediate national relevance and priority given the need to Safeguard Australia from invasive diseases. There is an urgency to undertake our research because global environmental change and increasing movements of people (particularly military personnel) from overseas regions where these diseases are endemic is increasing the vulnerability of northern Australia to the (re)establishment of mosquito borne diseases.Read moreRead less