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Category: Machine Learning
ACVT has strong capabilities in the field of machine learning and is developing new techniques and applying them to a range of diverse problem spaces. For example, work is underway in the area of automatic feature extraction and classification from satellite and aerial imagery using a supervised machine learning system. Of key importance is the development of robust classifiers and an associated framework by which to apply them to geospatial data. ACVT is also working on entity extraction and resolution from unstructured data sources. This involves the development of unsupervised clustering techniques which are able to be applied on a massive scale.
ARC Success! Congratulations to Prof Anton van den Hengel and Dr Anthony Dick
Congratulations to Anton and Anthony who have secured $330,000 of Discovery Project funding in the 2012 ARC round! TITLE: Learning to see in 3D PROJECT SUMMARY: The project aims to endow machine vision with an ability we, as humans, use almost constantly: to judge 3D properties from a 2D image. This extremely useful ability will be applied […]
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Improving yield through image-based structural analysis of cereals (LP110200971)
ACVT has been awarded a 3 year ARC Linkage Grant valued at $475,000. Bayer CropScience is the industry partner on the grant. The CIs are Prof. Anton van den Hengel and Prof. Mark Tester of the Plant Accelerator based at the University of Adelaide’s Waite Campus. Meeting the food requirements of a growing world population […]
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Another patent granted
Congratulations to Dr Gustavo Carneiro on the awarding of his latest US patent. The patent covers: A method for detecting fetal anatomic features in ultrasound images includes providing an ultrasound image of a fetus, specifying an anatomic feature to be detected in a region S determined by parameter vector .theta., providing a sequence of probabilistic boosting […]
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Content Based Image Retrieval
The World Wide Web is a visual place, full of images and video. As of September 2010, Flickr hosts over 5 billion photos, while over 2 billion videos are watched every day on Youtube. This is a vast store of information, but how can we find what we want? Currently, images are almost always identified […]
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Imaging cereals for increased crop yields
A news release about our recent ARC Linkage grant award: University of Adelaide computer scientists are developing image-based technology which promises a major boost to the breeding of improved cereal varieties for the harsher environmental conditions expected under climate change. Led by Professor Anton van den Hengel, Director of the Australian Centre for Visual Technologies […]
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Multi-model predictions of ecosystem flux under climate change based on novel genetic and image analysis methods (FS110200051)
ACVT is collaborating with University of Adelaide scientists to develop image analysis methods that can be applied to model biodiversity. Prof. Anton van den Hengel is a CI on the project being led by Prof. Andy Lowe. The ARC has awarded the University of Adelaide a Super-Science Fellowship valued at $556,800 to do this work. The […]
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2 Year Postdoctoral Position available from mid 2011
2-YEAR POSTDOCTORAL POSITION Australian Centre for Visual Technologies University of Adelaide South Australia Added Depth: Automated high level image interpretation Research areas: Computer Vision, Machine Learning The successful applicant will join an established and successful team, lead by Prof Anton van den Hengel, Dr Anthony Dick, Prof Philip Torr and Prof Simon Lucey, working on […]
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New academic appointed-Dr Chunhua Shen
Dr Chunhua Shen, previously of the NICTA Bionic Vision Project, has accepted a position in the School of Computer Science and the ACVT. Dr Shen is a leading Computer Vision expert and particularly strengthens ACVT expertise in Machine Learning.
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ACVT ARC Discovery Projects success
Profs David Suter and Anton van den Hengel were both awarded ARC Discovery Grants to begin in 2011. They are: Computer vision from a multi structural analysis framework, Prof D. Suter. Computer vision has applications in a wide variety of areas: security (video surveillance), entertainment (special effects), health care (medical imaging), and economy (improved automation and […]
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Added depth: automated high level image interpretation (DP110103521)
ACVT has been awarded a 3 year ARC Discovery Grant valued at $240,000. The CIs are Prof. Anton van den Hengel in collaboration with Dr Philip Torr of Oxford-Brookes University and Dr Simon Lucey of CSIRO. Automated image interpretation has been one of the landmark goals of Artificial Intelligence since its inception. It is only […]
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