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Latest News

Research Excellence Framework 2021
Research Excellence Framework 2021 Panel Membership Announced

Impartiality in AI and Machine Learning
The Global Future Councils held in Dubai in 2017 discussed the effect of large-scale adoption o...

Women in Mathematics
Only 4% of mathematics professors in the UK are female

Humans are not fooled
Humans are not fooled when they get called by software bots that can convincingly mimic the hum...

The musical mood of the nation
Examine the musical mood of the nation when contemplating changes to the Bank’s interest rate


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A window on the world of O.R.?
The “invisibility cloak” of science fiction is now fact, albeit with limitations. O.R. could claim to have had the power of invisibility for years, though not by desire; what we want is the opposite - a high-visibility jacket! Indeed, part of the mission of the OR Society is to help make our presence more visible. But perception involves both the observed and the observer. And all of us have open and hidden parts.

YOR18 – OR – A Twenty Twenty Vision
The 18th Young [to] OR Conference got off to a great start with the plenary session given by the President of the OR Society, Dr Geoff Royston. Antuela Tako, the chair of the organising committee, began the proceedings by telling the audience what had been planned for them and how to find out more about streams.

The Education & Research Committee
- Roles and Responsibilities: Brian Dangerfield (Liaison with ESRC)
Ruth Kaufman, Inside OR February 2013

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Posted on 02 November 2017

Artificial Intelligence

Large scale object recognition

One of the greatest successes of deep learning has been achieved in large scale object recognition with convolutional neural networks (CNNs). CNNs’ main power comes from learning data representations directly from data in a hierarchical layer based structure.

Researchers at the data science lab at Warwick Business school, recently took more than 200,000 images of places in the UK, placed them on the scenic-or-not website and then got one and half million people to rate them for their beauty.
The model was then tested on more than 200,000 photographs of London that it had not seen before. It was fascinating to see that the model understood that bridges and historical architecture increase the perceived beauty of a scene, while grass and greenery is not necessarily scenic.
“Our previous results make it clear that scientists and policymakers alike need measurements of environmental beauty, not just measurements of how green places are. Games like scenic-or-not can help us collect millions of ratings from humans, but having a model which can automatically tell us whether a place is beautiful or not opens up completely new horizons.”

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