Thursday, September 15, 2016
Link to paper:
Wi-Fi signals are typically information carriers between a transmitter and a receiver. In this paper, we show that Wi-Fi can also extend our senses, enabling us to see moving objects through walls and behind closed doors. In particular, we can use such signals to identify the number of people in a closed room and their relative locations. We can also identify simple gestures made behind a wall, and combine a sequence of gestures to communicate messages to a wireless receiver without carrying any transmitting device. The paper introduces two main innovations. First, it shows how one can use MIMO interference nulling to eliminate reflections off static objects and focus the receiver on a moving target. Second, it shows how one can track a human by treating the motion of a human body as an antenna array and tracking the resulting RF beam. We demonstrate the validity of our design by building.
Link to paper:
Link to project web-page:
στις 9:02 PM
Friday, August 5, 2016
Wednesday, March 2, 2016
This is a cleaning robot that will shortly be deployed in the Gare de Lyon. I wander how this is considered from the socialist party of François Hollande. Of course, cleaning jobs will be shortened but engineering posts will be opened, but in the end, what is the real (economic and societal) cost for the introduction of such robotic technology?
On the other hand, a robot "valet" that carries your suitcases and follows you, is indeed within the french culture and in my opinion should have no problem to be accepted as technology...
στις 3:02 PM
Saturday, February 20, 2016
------ http://www.deepart.io/ ------
Abstract: In fine art, especially painting, humans have mastered the skill to create unique visual experiences through composing a complex interplay between the content and style of an image. Thus far the algorithmic basis of this process is unknown and there exists no artificial system with similar capabilities. However, in other key areas of visual perception such as object and face recognition near-human performance was recently demonstrated by a class of biologically inspired vision models called Deep Neural Networks. Here we introduce an artificial system based on a Deep Neural Network that creates artistic images of high perceptual quality. The system uses neural representations to separate and recombine content and style of arbitrary images, providing a neural algorithm for the creation of artistic images. Moreover, in light of the striking similarities between performance-optimised artificial neural networks and biological vision, our work offers a path forward to an algorithmic understanding of how humans create and perceive artistic imagery.
στις 4:31 PM