"The Great Convergence" or How ML/DL is Disrupting Sensor Design

On Wednesday night, we had the Paris Machine Learning meetup. It was, shall we say, unusual and eventful. More on that later. Because of the flu, two of our speakers could not make it and we had to scramble to put more presentations in the schedule in short order. I rapidily put together one presentation that summarized some of my current thoughts about sensor/hardware design. Because the meetup was eventful, I decided that after three hours, we really needed to go eat and be merry and shelved that presentation. I am not sure I will be able to present it anytime soon as the next meetup will be about hardware for Machine Learning and will probably not be a good fit. So here it is:

 Igor Carron, "The Great Convergence" or How ML/DL is disrupting sensor design.

I describe through three examples how sensor design is being disrupted by new Machine Learning Techniques.

References:

• Tomasz Malisiewicz, From feature descriptors to deep learning: 20 years of computer vision
• Jack Clark, Why AI development is going to get even faster ,
• David Beyer, Future of Machine Intelligence,
• The Great Convergence tag on Nuit Blanche,  
• « Making Hyperspectral Imaging Mainstream » 
• Sunday Morning Insight: A Quick Panorama of Sensing from Direct Imaging to Machine Learning
  

Join the CompressiveSensing subreddit or the Google+ Community or the Facebook page and post there !
Liked this entry ? subscribe to Nuit Blanche's feed, there's more where that came from. You can also subscribe to Nuit Blanche by Email, explore the Big Picture in Compressive Sensing or the Matrix Factorization Jungle and join the conversations on compressive sensing, advanced matrix factorization and calibration issues on Linkedin.