Machine Learning

Macrophenological Dynamics from Citizen Science Plant Occurrence Data
Phenological shifts across plant species is a powerful indicator to quantify the effects of climate change. Today, mobile applications …
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Imputing Missing Data in Plant Traits: A Guide to Improve Gap-filling
Abstract Aim Globally distributed plant trait data are increasingly used to understand relationships between biodiversity and ecosystem …
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Classification Characteristics of Fine Motor Experts Based on Electroencephalographic and Force Tracking Data
The application of machine learning techniques provides a data-driven approach for a deeper understanding of the development and …
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Spatially Autocorrelated Training and Validation Samples Inflate Performance Assessment of Convolutional Neural Networks
Deep learning and particularly Convolutional Neural Networks (CNN) in concert with remote sensing are becoming standard analytical …
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Classification of Visuomotor Tasks Based on Electroencephalographic Data Depends on Age-Related Differences in Brain Activity Patterns
Classification of physiological data provides a data driven approach to study central aspects of motor control, which changes with age. …
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Discovering Differential Equations from Earth Observation Data
Modeling and understanding the Earth system is a constant and challenging scientific endeavour. When a clear mechanistic model is …
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Detection of Xylella Fastidiosa Infection Symptoms with Airborne Multispectral and Thermal Imagery: Assessing Bandset Reduction Performance from Hyperspectral Analysis
Xylella fastidiosa (Xf) is a harmful plant pathogenic bacterium, able to infect over 500 plant species worldwide. Successful …
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Detection of Xylella Fastidiosa Infection Symptoms with Airborne Multispectral and Thermal Imagery: Assessing Bandset Reduction Performance from Hyperspectral Analysis
Predicting Forest Cover in Distinct Ecosystems: The Potential of Multi-Source Sentinel-1 and -2 Data Fusion
The fusion of microwave and optical data sets is expected to provide great potential for the derivation of forest cover around the …
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A High-Performance and in-Season Classification System of Field-Level Crop Types Using Time-Series Landsat Data and a Machine Learning Approach
Accurate and timely spatial classification of crop types based on remote sensing data is important for both scientific and practical …
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Reverse Engineering Model Structures for Soil and Ecosystem Respiration: The Potential of Gene Expression Programming
Abstract. Accurate model representation of land–atmosphere carbon fluxes is essential for climate projections. However, the exact …
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