High Definition image classification in Geoscience using Machine Learning

September 25, 2020 Β· Entered Twilight Β· πŸ› arXiv.org

πŸŒ… TWILIGHT: Old Age
Predates the code-sharing era β€” a pioneer of its time

"Last commit was 7.0 years ago (β‰₯5 year threshold)"

Evidence collected by the PWNC Scanner

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.
Community shame:
Not yet rated
Community Contributions

Found the code? Know the venue? Think something is wrong? Let us know!

πŸ“œ Similar Papers

In the same crypt β€” Image & Video Processing