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Originally Posted by Turing'sEgo
Based on my experience with deep learning, as well as many of my friend, it is really hit or miss when it comes to if a model will work or or not.
How many different architectures did you try before you decided on this?
What were the specs of the computer you trained on? (And how long did it take?)
Did you find a discrepancy between boulder detection in your space as opposed to at competition?
Moving forward, I suggest taking a look at the winner of ilsvrc 2015.
Excellent work 900. I always look forward to these every year.
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I'll answer these as best as I can but I'll see about getting a student to add clarity.
We tried and are trying a lot of things. I doubt we will ever find "the perfect model". It's an ever-evolving system but we're getting a lot better at generalizing it and making it repeatable, which is good.
The computer we train on is a 12 core Xeon 2680v3 with 32GB of DDR4. Most of the training is done on an Nvidia Titan X. We've run into problems based on the SSD speeds though and the computer will see a storage upgrade in the coming months to help speed things up further. It's a zippy machine though. Our training can take anywhere from 1 to 8 hours depending on a bunch of factors (though we've had a few sessions take from 12-24 hours I believe). I'll see if I can get a student to be more specific about this. I own the system but the students use it for this. I use it for running VMs inside of sandboxes so I can take them to pieces and experiment for work (I am a Solutions Architect for a big IT company).
We did find discrepancies and we've done our best to minimize them. We explain the methodology we use for capturing game piece images in the paper. It's a chromakey solution that we add digital noise to. It's surprisingly good once you get it tuned in.
We'll definitely take a look at it. I think from an architecture standpoint the next big leap for us will be to roll this into ROS on the Jetson to provide a better wrapper for all of it.
Thanks! Glad to see some positivity.
