Ocean Color remote sensing has a great importance in monitoring of aquatic environments.
The number of optical imaging sensors onboard satellites has been increasing in the past …

Kernel methods are powerful machine learning techniques which use generic non-linear
functions to solve complex tasks. They have a solid mathematical foundation and exhibit …

Gaussian process regression (GPR) has experienced tremendous success in biophysical
parameter retrieval in the past years. The GPR provides a full posterior predictive distribution …

Kernel dependence measures yield accurate estimates of nonlinear relations between
random variables, and they are also endorsed with solid theoretical properties and …

Accurately predicting wave height has a significant impact on offshore production and
marine transportation. Numerical model predictions are the most commonly used wave …

This work utilizes Machine Learning (ML) regression and feature ranking techniques for
water quality monitoring from remotely sensed data. The investigated regression methods …

The fishing and aquaculture industry is one of the largest industries of Norway. Enhanced
knowledge of the distribution of fish in the ocean is important for an economical and …