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Old 17th September 2019, 07:53 PM   #10
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Join Date: Aug 2006
Location: The Great Midwest
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Originally Posted by JeffS
I work with machine learning for classifying land cover types (forest, grassland etc) on satellite imagery to better under changes over time, like deforestation or development. This particular paper is using edge detection outputs to classify keris types. As such this will broadly allow it to classify broad groups that can be distinguishable with 2-D profile (silhouette) information. As Ariel says, this an interesting academic exercise but certainly can't add to keris understanding which is clearly far more subtle than profile ratios.

I have to point out that you cannot really determine the dhapur of a keris by silhouette edge detection alone. Such a method cannot show, for instance, if the keris has tikel alis, blumbangan, sogokan or other interior keris elements that are essential for proper identification. I am still having problems finding a practical purpose for this methodology.
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