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Seems like a bad idea in hindsight! Any system like this should be considering multiple factors, including the shape and size, as well as evaluating the behavio
by dkdbejwi383 5y ago
Seems like a bad idea in hindsight! Any system like this should be considering multiple factors, including the shape and size, as well as evaluating the behaviour of other drivers to see if the perceived instruction seems reasonable. After all, that's what we do as humans.
- dagw 5y agoOne of the core problems with machine learning is that we often don't really know why the model does what it does. We train the neural network on 100000 images of road sign, 5000 of which are stop signs and we know it will identify stop signs, but we don't know what it is that makes the algorithm think something actually is a Stop sign. Is it the color, the shape, the word "Stop"? The training set had red octagonal signs and signs with numbers, but no red octagonal signs with numbers. Since the the model had never seen a sign with just two big digits that wasn't a speed limit sign it decides that the numbers was more significant than the shape or color and went with that. What this shows is how important it is to include intentionally adversarial data in your training set if you want your model to be robust in 'unexpected' situations.