High Definition image classification in Geoscience using Machine Learning
September 25, 2020 Β· Entered Twilight Β· π arXiv.org
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Repo contents: .gitignore, README.md, demo, flask, package-lock.json, package.json, public, server, src, yarn.lock
Authors
Yajun An, Zachary Golden, Tarka Wilcox, Renzhi Cao
arXiv ID
2010.03965
Category
eess.IV: Image & Video Processing
Cross-listed
cs.CV
Citations
0
Venue
arXiv.org
Repository
https://github.com/zachgolden/geoai
Last Checked
2 months ago
Abstract
High Definition (HD) digital photos taken with drones are widely used in the study of Geoscience. However, blurry images are often taken in collected data, and it takes a lot of time and effort to distinguish clear images from blurry ones. In this work, we apply Machine learning techniques, such as Support Vector Machine (SVM) and Neural Network (NN) to classify HD images in Geoscience as clear and blurry, and therefore automate data cleaning in Geoscience. We compare the results of classification based on features abstracted from several mathematical models. Some of the implementation of our machine learning tool is freely available at: https://github.com/zachgolden/geoai.
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