Landmine or Coke Can: Deep Learning with GPR Data

Time Slices5_Grid9One of the projects that has taken up a lot of my time the past few months is that of a UAV (drone) based Ground Penetrating Radar (GPR) system. There are a number of applications for this but the one we have been focussing on initially is landmine and UXO clearance. The elements that make up such a system are quite broad. Ranging from sensor design, UAV integration, positioning, terrain following to data analysis. As with many drone projects most of the attention tends to go to the hardware and the flying. While that is certainly important and I have been working on those elements too, the whole system is only as good as the quality and interpretability of the data you get back. That is key. With this post I’ll aim to give a brief summary of the work I have been leading on this front.

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Where are the engineering hipsters?

enghipsterIts late and I’m on my way back from the final demo evening of the Advanced Skills Initiative (ASI). The ASI programme takes disgruntled academics and puts them through an intensive 8 week data science course so they can move into the bustling data science job market. I was a mentor on the machine learning front and it was great to see the fellows evolve and battle through their projects.

One thing struck me though. Something that has been bugging me for a while. Projects pitched at events and meetups like this invariably cover product recommendation, preference learning, financial NLP, churn prediction, adclick prediction, social media trending analysis, etc.

As somebody who likes tangible things, I can’t help but wonder. Where are the projects & startups from aerospace, automotive, marine and other engineering disciplines? Why aren’t we seeing projects from Airbus on smart IVHM, from Jaguar on crumple zones, from Reaction Engines on engine performance, from ASV on marine autopilots, from Princess on vibration control, from McLaren on race strategy, from Dyson on path planning, etc. I personally find these things hugely interesting and fascinating topics. The possibilities for data science / machine learning are endless, prognostics being the obvious example.

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