Principal Component Analysis for Place Recognition
نویسندگان
چکیده
We present a hybrid neural network model to solve a place recognition problem. The front end is a self-organizing net equivalent to a principal component analyzer; the back end is a feed-forward net with backpropagation, i.e. supervised learning. A conndence level greater than 0.9 was reported as the net correctly recognized a repertoire of pictures it had not seen before.
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