Dimensionality Reduction with Image Data
نویسندگان
چکیده
A common objective in image analysis is dimensionality reduction. The most common often used data-exploratory technique with this objective is principal component analysis. We propose a new method based on the projection of the images as matrices after a Procrustes rotation and show that it leads to a better reconstruction of images.
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تاریخ انتشار 2004