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Number one in Semantic Segmentation
Congratulations to Zifeng Wu and Chunhua Shen on having made it to the top of the Cityscapes leaderboard again.
Medical Machine Learning in The Conversation
We just had a piece on medical machine learning published in the Conversation.
[Read more about Medical Machine Learning in The Conversation]
AIML technology gets FDA approval
AIML (formally ACVT) has been working with LBT Innovations, a South Australian medical device company, for more than 5 years on a new form of medical device to automate the reading of Agar plates.
AIML medical imaging technology achieves 98% in FDA trials
A ten-week pivotal clinical trial at TriCore Reference Laboratories in New Mexico during July and August 2015 tested APAS against a panel of microbiologists. C
[Read more about AIML medical imaging technology achieves 98% in FDA trials]
Number two in ImageNet Scene Parsing Challenge 2016
We’ve had another great year in the ImageNet competition.
[Read more about Number two in ImageNet Scene Parsing Challenge 2016]
AIML joins the Australian Driverless Vehicle Initiative
The AIML (formally ACVT) has joined the Australian Driverless Vehicle Initiative (ADVI), the peak body for driverless vehicles in Australia.
[Read more about AIML joins the Australian Driverless Vehicle Initiative]
A new Machine Learning result in Quantum Physics
John Bastian and Anton van den Hengel are among the authors of a new paper just published in Nature Scientific Reports.
[Read more about A new Machine Learning result in Quantum Physics]
We're in the top 5 groups the world
The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) is double blind reviewed (on full papers), and has the best citation rate in the field of computer vision and pattern recognition, according to the h5-index, a citation measure for the recent five years.
10 PAMIs and 28 CVPRs in just over a year
The AIML (formally ACVT) has had 10 journal articles published in IEEE Pattern Analysis and Machine Intelligence, and 28 papers in the IEEE Conference on Computer Vision and Pattern Recognition, in the 16 months since January 2015.
We beat Google at ImageNet Detection
The ImageNet Object Detection results are out, and we did extremely well!