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Joao Paulo Papa edited abstract.tex
over 8 years ago
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\begin{abstract}
Testando. Unsupervised land-use/cover classification is of great interest, since it becomes even more difficult to obtain high-quality labeled data. Still considered one of the most used clustering techniques, the well-known $k$-means plays an important role in the pattern recognition community. Its simple formulation and good results in a number of applications have fostered the development of new variants and methodologies to address the problem of minimizing the distance from each dataset sample to its nearest centroid (mean).
\end{abstract}
