Shape recognition of volcanic ash by simple convolutional neural network
June 22, 2017 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Daigo Shoji, Rina Noguchi
arXiv ID
1706.07178
Category
physics.geo-ph
Cross-listed
cs.CV
Citations
0
Venue
arXiv.org
Last Checked
3 months ago
Abstract
Shape analyses of tephra grains result in understanding eruption mechanism of volcanoes. However, we have to define and select parameter set such as convexity for the precise discrimination of tephra grains. Selection of the best parameter set for the recognition of tephra shapes is complicated. Actually, many shape parameters have been suggested. Recently, neural network has made a great success in the field of machine learning. Convolutional neural network can recognize the shape of images without human bias and shape parameters. We applied the simple convolutional neural network developed for the handwritten digits to the recognition of tephra shapes. The network was trained by Morphologi tephra images, and it can recognize the tephra shapes with approximately 90% of accuracy.
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