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Real transcript from a Stanford CS231N lecture — timestamped and searchable.
Welcome to CS231N. Today we're going to talk about the history of computer vision and why we think deep learning has been such a transformative approach to these problems.
So let's start by thinking about — why is vision hard? The human visual system is extraordinarily powerful. We process something like 10 to the 14 synaptic operations per second.
One of the earliest and most influential works in understanding biological vision was by Hubel and Wiesel in 1959. They recorded from neurons in the visual cortex of cats...
What they found was that there are simple cells — neurons that respond to edges at a particular orientation and location — and complex cells that respond to the same features but are position-invariant.
This idea of a hierarchy of features, going from simple to complex, directly inspired the design of convolutional neural networks decades later.
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