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please look at this - interesting for our prospective exercise (LS)

impressive, particularly if it works like it does in the video the whole time. paper here http://mi.eng.cam.ac.uk/~qp202/

Well, impressive indeed... have to try it out...

pretty impressive stuff!

LSTMs: that was also the first thing in the paper that caught my attention! :) I hadn't seen them in the wild in years... My oversight most likely. The paper seems to be getting ~100 citations a year. Someone's using them.

There are a few papers on them. Though you have to be lucky to get them to work. The backprop is horrendous.

DeepMind actually got a comp-sci paper into nature...

Inspired by the work that was done at the ACT, I continued working on optical flow landing at TU Delft. Today Bio & Bio published my article on a new theory that allows drones to see distances with a single camera. It shows that drones approaching an object with an insect-inspired vision strategy become unstable at a specific distance from the object. Turning this weakness into a strength, drones can actually use the timely detection of that instability to estimate distance. The new theory will enable further miniaturization of autonomous drones and provides a new hypothesis on flying insect behavior. Video: https://www.youtube.com/watch?v=Fm7SMJp8EA4&feature=youtu.be Article: http://iopscience.iop.org/article/10.1088/1748-3190/11/1/016004

Computer vision researchers have uncovered a world of visual signals hiding in our midst, including subtle motions that betray what's being said and faint images of what's around a corner.

In the Planetary Science Vision 2050 Workshop a cool concept for a magnetic dipole sitting at Mars L1 with an estimated field of 1-2 Tesla was proposed to shield Mars from Solar Winds and provide an elementary magnetic shielding to Mars.

"Hinton's new approach, known as capsule networks, is a twist on neural networks intended to make machines better able to understand the world through images or video. In one of the papers posted last week, Hinton's capsule networks matched the accuracy of the best previous techniques on a standard test of how well software can learn to recognize handwritten digits." Links to papers: https://arxiv.org/abs/1710.09829 https://openreview.net/forum?id=HJWLfGWRb&noteId=HJWLfGWRb

impressive!

seems a very impressive guy :"Hinton formed his intuition that vision systems need such an inbuilt sense of geometry in 1979, when he was trying to figure out how humans use mental imagery. He first laid out a preliminary design for capsule networks in 2011. The fuller picture released last week was long anticipated by researchers in the field. "Everyone has been waiting for it and looking for the next great leap from Geoff," says Kyunghyun Cho, a professor"

Making a jumping spider eye with nanophotonics and computer vision: depth from defocus with an integrated mentalens sensor! Some in the ACT might be familiar with the concept...