A Comparison of Classification Methods for Large Imagery Data Sets
نویسندگان
چکیده
Classification is an important field with many applications. In particular, the classification of digital imagery has important applications in the mapping community. In this paper the authors compare five different classification methods on LANDSAT imagery of Australia and multispectral imagery of south-central Virginia: support vector machines, neural networks, nearest-neighbor, discriminant analysis, and classification trees. The authors also investigate computational limits of existing software for these five methods. Results are shown and discussed. .
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