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TAG: Competition

Award for Excellence in Collaboration

The collaboration between ACVT and LBT Innovations won the SA Science Excellence award for Research Collaboration for the development of that APAS technology. APAS is an automated agar plate reader, which promises to greatly reduce the cost of this critical pathology procedure. APAS achieve first-in-class FDA approval last year.  

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We’re number one in VQA 2.0

A team led by Damien Teney (ACVT) and Peter Anderson (ACRV, ANU, and Microsoft) has just placed first in the VQA 2.0 challenge. Other members of the team include David Golub from Stanford, Po-Seng Huang, Lei Zhang and Xiaodong He from Microsoft, and Anton van den Hengel from ACVT. The leaderboard is here.

Posted in Machine Learning, News, Visual Question Answering | Tagged , , , , |

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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.  There will be more submitted as the deadline approaches, but we’ll improve our performance also.  So we’re not there yet, but we’re in a very good position. The task of Visual […]

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Number 1 in Semantic Segmentation

Congratulations to Zifeng and Chunhua on having made it to the top of the Cityscapes leaderboard again. Cityscapes is a semantic segmentation dataset of city scenes, and a hotly contested international challenge.  The challenge is to separate the pixels belonging to different classes of objects.  Semantic Segmentation is one of the fundamental challenges in computer […]

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Great ImageNet Detection Results

Last week was the deadline for the ImageNet Large Scale Visual Recognition Challenge (ILSVRC 2015) large-scale object detection task. This is the primary challenge for image-based object detection.  The challenge requires that you detect 200 classes of objects in a set of test images. For each image, algorithms must produce a set of annotations (ci,si,bi)of […]

Posted in Machine Learning, News, Object Recognition, Research | Tagged , , , |

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