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Found 4 papers, 0 papers with code
Ocean Eddy Identification and Tracking using Neural Networks
We show the detection and tracking results on sea level anomalies (SLA) data from the area of Australia and the East Australia current, and compare our two eddy detection and tracking approaches to identify the most robust and objective method.
Archetypal Analysis for Sparse Representation-based Hyperspectral Sub-pixel Quantification
In our experiments, the estimation of the automatically derived elementary spectra is compared to the estimation obtained by a manually designed spectral library by means of reconstruction error, mean absolute error of the fraction estimates, sum of fractions, $R^2$, and the number of used elementary spectra.
Deep Self-taught Learning for Remote Sensing Image Classification
This paper addresses the land cover classification task for remote sensing images by deep self-taught learning.
Sea Level Anomaly Prediction using Recurrent Neural Networks
We develop a combination of a convolutional neural network (CNN) and a recurrent neural network (RNN) to ana-lyse both the spatial and the temporal evolution of sea level and to suggest an independent, accurate method to predict interannual sea level anomalies (SLA).
