论文标题
使用机器学习中的高清图像分类
High Definition image classification in Geoscience using Machine Learning
论文作者
论文摘要
高清（HD）用无人机拍摄的数字照片广泛用于地球科学研究。但是，模糊的图像通常是在收集的数据中拍摄的，并且需要大量时间和精力将清晰的图像与模糊图像区分开。在这项工作中，我们应用机器学习技术，例如支持向量机（SVM）和神经网络（NN），将地球科学中的高清图像分类为清晰且模糊，因此在地球科学中自动化数据清洁。我们根据从几个数学模型中抽象的特征比较分类结果。我们的机器学习工具的某些实现可免费获得：https：//github.com/zachgolden/geoai。
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.
