News: Research
Media Release: Tetris-like program could speed breast cancer detection
Researchers from the University of Adelaide’s Australian Institute for Machine Learning (AIML) are developing a fully-automated medical image analysis program to detect breast tumours. The program uses a unique style to focus on the affected area.
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Number one in the world in Visual Question Answering again, for now
Entries for the latest VQA v2 challenge close on Monday morning, and we’re currently number one amongst the entries that have been submitted thus far.
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Another great CVPR result
The group had 11 CVPR papers accepted this year, which is another incredible result.
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.
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Number two in ImageNet Scene Parsing Challenge 2016
We’ve had another great year in the ImageNet competition.
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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.
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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!
