1.

Pipeline for imaging, extraction, pre-processing, and processing of time-series hyperspectral data for discriminating drought stress origin in tomatoes

In this paper, we present a process for image acquisition, pre-processing and processing of hyperspectral data in a time series to separate the source of drought stress in tomatoes. Using a combination of spectral data in a time series, data dimensionality reduction methods, and machine learning, we reliably distinguished between biotic and abiotic stress in tomatoes.

COBISS.SI-ID: 5710952

2.

Natural color representation of Sentinel-2 data

In this paper we define the natural color product, propose two efficient approaches for computing it, analyze the results, and implement the products on a satellite imagery service for interactive use. Our algorithms work on a per-pixel basis and hence parallelize naturally. The presented approaches are general and not limited to Sentinel-2 data.

COBISS.SI-ID: 39990533