53 citations · 66 across the 2 of their papers we have counts for
7 papers
Application of Different Simulated Spectral Data and Machine Learning to Estimate the Chlorophyll a Concentration of Several Inland Waters
Philipp M. Maier, Sina Keller
Water quality is of great importance for humans and for the environment and has to be monitored continuously. It is determinable through proxies such as the chlorophyll a concentra…
Estimating Chlorophyll a Concentrations of Several Inland Waters with Hyperspectral Data and Machine Learning Models
Philipp M. Maier, Sina Keller
Water is a key component of life, the natural environment and human health. For monitoring the conditions of a water body, the chlorophyll a concentration can serve as a proxy for…
SuSi: Supervised Self-Organizing Maps for Regression and Classification in Python
Felix M. Riese, Sina Keller
In many research fields, the sizes of the existing datasets vary widely. Hence, there is a need for machine learning techniques which are well-suited for these different datasets.…
Soil Texture Classification with 1D Convolutional Neural Networks based on Hyperspectral Data
Felix M. Riese, Sina Keller
Soil texture is important for many environmental processes. In this paper, we study the classification of soil texture based on hyperspectral data. We develop and implement three 1…
Machine learning regression on hyperspectral data to estimate multiple water parameters
Philipp M. Maier, Sina Keller
In this paper, we present a regression framework involving several machine learning models to estimate water parameters based on hyperspectral data. Measurements from a multi-senso…
Developing a machine learning framework for estimating soil moisture with VNIR hyperspectral data
Sina Keller, Felix M. Riese, Johanna Stötzer +2
In this paper, we investigate the potential of estimating the soil-moisture content based on VNIR hyperspectral data combined with LWIR data. Measurements from a multi-sensor field…