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The World Through the Eyes of a Self-driving Car

This article overall talks about "Visualizing which part of an image a neural network uses to recognize traffic lights".  He talks about how he ran some tests on a ConvNet (Convolutional Neural Network) to test how well it did on recognizing the traffic lights and talks about how the neural network recognizes the traffic lights.

"In this post I describe a very simple and useful method for visualizing what part of an image the network uses for its prediction. The approach involves occluding parts of the image and seeing how that changes the network’s prediction. This approach has been described in “Visualizing and Understanding Convolutional Networks”. Self-driving cars today use much more sophisticated methods for detecting objects in a scene, as well as many more sensors as inputs. The ConvNet we examine throughout the post should be seen as a simplified version of what self-driving cars actually use. Nonetheless, the visualization method described in this post can be useful and adapted for different kinds of neural network applications."

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