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An automatic method for the selection of subsets of images, both modern andhistoric, out of a set of landmark large images collected from the Internet ispresented in this paper. This selection depends on the extraction of dominantfeatures using Gabor filtering. Features are selected carefully from apreliminary image set and fed into a neural network as a training data. Themethod collects a large set of raw landmark images containing modern andhistoric landmark images and non-landmark images. The method then processesthese images to classify them as landmark and non-landmark images. Theclassification performance highly depends on the number of candidate featuresof the landmark.

Image Subset Selection Using Gabor Filters and Neural Networks