This paper further compared 4 image classification models such as decision tree classifier DTC, non-linear support vector machine (SVM), k-nearest neighbors ( ...
In this paper, Qijn dataset from Landsat 8 are used to train model, then five classification models are compared for accuracies, F1 scores and precision-recall ...
Aug 14, 2024 · Age and sex-specific IRs using the 2010 classification criteria at baseline were similar to cumulative IRs applying the 1987 criteria up to 5 ...
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CoastSat is an open-source software toolkit written in Python that enables the user to obtain time-series of shoreline position at any sandy coastline ...
CoastSat is an open-source software toolkit written in Python that enables users to obtain time-series of shoreline position at any coastline worldwide.
Our results demonstrate the efficiency of the SVM model in mapping sandy beaches (User's accuracy: 96%, Kappa coefficient: 0.93). We identified 3,444 beaches in ...
We classify methods into four groups: water indices, edge detection, thresholding methods, and machine learning. Moreover, we summarize the extraction methods ...
Comparison of support vector machine and object based classification methods for coastline detection. K. Kalkan, B. Bayram, D. Maktav, and F. Sunar. K. Kalkan.
Missing: Models COASTSAT.
CoastSat is an open-source software toolkit that enables user to obtain time-series of shoreline position at any sandy coastline worldwide.
In this notebook the CoastSat classifier is trained using satellite images from new sites. This can improve the accuracy of the shoreline detection if the users ...
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