Using Neural Networks to Learn Features for Computer Vision
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The PI has considerable experience in computer recognition of objects           which, if improved, could be of considerable value to areas like                robotics and industrial automation.  The PI proposes to improve the             quality of features used in object recognition, by using newly                  developed methods for supervised learning taken from the "back                  propagation" school of neuroengineering.  The chances of success in             this work are considered quite good.
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