Technology: How Neural Networks Can See What We're Doing Through Walls - PressFrom - US
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Technology How Neural Networks Can See What We're Doing Through Walls

00:15  10 october  2019
00:15  10 october  2019 Source:   popularmechanics.com

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Advanced neural networks that use radio wave imaging to see have the exact opposite problem. Now, a new technique developed by researchers at The new method uses radio waves to train a neural network to spot patterns of activity that can’t be viewed in visible light, according to a paper, titled

We are used to seeing characters break through walls and buildings with just a gaze but could you The neural network has been developed in such a way that it can sense and analyze radio signals They put together a database of thousands of images which had people doing things like walking

a close up of a sign: A new technique developed by MIT researchers harnesses radio waves to help neural networks spot what someone is doing through a wall.© Li et. al (2019) A new technique developed by MIT researchers harnesses radio waves to help neural networks spot what someone is doing through a wall.
  • A new technique developed by MIT researchers harnesses radio waves to help neural networks spot what someone is doing through a wall.
  • Researchers trained a neural network to recognize people's activity patterns by inputting films of their actions, shot both in visible-light and radio waves.
  • Don’t worry: The low-res tech isn’t able to identify people.

Humans can spot patterns of activity, but we can’t see through walls. Advanced neural networks that use radio wave imaging to see have the exact opposite problem. Now, a new technique developed by researchers at Massachusetts Institute of Technology is helping the neural networks see the world a little more clearly.

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What is a neural network ? To get started, I'll explain a type of artificial neuron called a perceptron. Learning algorithms sound terrific. But how can we devise such algorithms for a neural network ? For example, suppose we ' re trying to determine whether a handwritten image depicts a "9" or not.

The neural networks that we are going to considered are strictly called artificial neural networks Taking what we explain about the structure of a neural network , weights and bias need to be first Now, how do we apply this to our neural network in python?. Here, we can see step by step the

The new method uses radio waves to train a neural network to spot patterns of activity that can’t be viewed in visible light, according to a paper, titled “Making the Invisible Visible: Action Recognition Through Walls and Occlusions,” recently posted to the preprint server arXiv. The researchers say the tech is especially helpful in difficult conditions, such as when someone is obscured in darkness or fog or around a corner.

Participants’ actions filmed in both visible-light (above) and radio waves (below). Note the algorithm’s predicted action. © Li et. al (2019) Participants’ actions filmed in both visible-light (above) and radio waves (below). Note the algorithm’s predicted action.

“Our model takes radio frequency (RF) signals as input, generates 3D human skeletons as an intermediate representation, and recognizes actions and interactions of multiple people over time,” the MIT researchers write in the paper.

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But that’s what neural networks are for. Your classic machine learning relies on labeling to train an AI. Seeing through walls would also be handy for robots—they could peer around corners to avoid running into How WIRED lost 0,000 in Bitcoin. Did science miss its best shot at an AIDS vaccine?

The seeing - through -the- wall part is done using an RF transmitter and receiving antennas, which isn’t very new. The neural networks spit out pose estimations of where people’s heads, shoulders, elbows I think the US Navy is already doing this but with towed array passive sonar versus radar.

The scientists used visual-light imagery to train a radio wave vision system they created. By recording the same video in both visible light and radio waves, the researchers can sync the videos and train a neural network, which can be coached to recognize human activity in visible light, to spot the same activity when it's picked up using radio waves.

The catch? It takes time for the system to learn to differentiate a person from their surroundings. To ameliorate this issue, the team created an additional set of training data videos composed of 3D stick figure models that replicated the humans in the film and fed those to the neural network, too.

Using this imagery as a training set, the neural network was able to track the actions of hidden people in both visible light and using radio waves.

There’s no reason to be concerned about privacy. Yet. At the moment, the technology is low resolution, so it can’t identify people by their faces. In fact, it’s been proposed as a more secure alternative to visible light cameras, which can easily pick up a number of details.

Source: MIT Technology Review

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