The detection and identification of plant diseases is crucial for an appropriate and targeted
application of plant protection measures in crop production. Recently, intensive research …

This paper provides an overview over the application of scanning macro-XRF with mobile
instruments for the investigation of historical paintings. The method is compared to …

Nonnegative matrix factorization (NMF) has become a widely used tool for the analysis of
high-dimensional data as it automatically extracts sparse and meaningful features from a set …

In this paper, we study the nonnegative matrix factorization problem under the separability
assumption (that is, there exists a cone spanned by a small subset of the columns of the …

Identifying the underlying structure of a data set and extracting meaningful information is a
key problem in data analysis. Simple and powerful methods to achieve this goal are linear …

Background The detection and characterization of resistance reactions of crop plants
against fungal pathogens are essential to select resistant genotypes. In breeding practice …

Behavioral data from computer games can be exceptionally high-dimensional, of massive
scale and cover a temporal segment reaching years of real-time and a varying population of …

While all kinds of mixed data---from personal data, over panel and scientific data, to public
and commercial data---are collected and stored, building probabilistic graphical models for …

Modern phenoty** and plant disease detection methods, based on optical sensors and
information technology, provide promising approaches to plant research and precision …

Background Phenoty** is a bottleneck for the development of new plant cultivars. This
study introduces a new hyperspectral phenoty** system, which combines the high …