Content tagged neural-network
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AWS has recently introduced the P3 instances. They come with Tesla V100 GPUs, so I decided to run a little benchmark to see how well they perform compared to my workstation (GeForce 1080 Ti) when training neural networks.
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There was no understandable and straightforward implementation of SSD in TensorFlow, so I decided to make one. The original paper assumes familiarity with related research, so I needed to plow through several additional papers and a ton of source code to understand what's going on here. This post is an attempt to provide all that missing context in one place.
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I have recently stumbled upon two articles on running TensorFlow on CPU setups and decided to check how well that works for the models I use. The results were somewhat unexpected.
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Semantic segmentation is a process of dividing an image into sets of pixels sharing similar properties and assigning one of the pre-defined labels to each of these sets. Or, in other words, you get a picture, and you're supposed to tell which pixels constitute a car and which constitute the pedestrians. Fun stuff.
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You get to drive a car in a game capturing some images and the corresponding steering angle. You then use that data to build a neural network that spits out a steering angle for an input image such that the computer can drive the same car in the same game. The computer learns how to drive from you, hence behavioral cloning.