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Tools for Automated Rock Descriptionтезисы доклада
- Авторы: Baraboshkin E., Orlov D., Koroteev D.
- Сборник: First EAGE Digitalization Conference and Exhibition
- Тезисы
- Год издания: 2020
- Издательство: European Association of Geoscientists and Engineers
- Местоположение издательства: Netherlands
- DOI: 10.3997/2214-4609.202032061
- Аннотация: The algorithms for the classification of images are well developed in recent years. They work well when the classes are clearly defined between each other. The geological classes are not like that because they can be observed in different scales and classification paradigms. To tackle this problem, we compare different feature extraction techniques and classification (semi- and supervised) algorithms. We present methods which help to increase the accuracy of rock type classification.
- Добавил в систему: Барабошкин Евгений Евгеньевич