%0 Generic
%A Wen, Junhan
%A de Weerdt, Mathijs
%A Abeel, Thomas
%A Verschoor, Camiel
%A Schuddebeurs, LIsanne
%A Walraven, Klaas
%A Jochems, Stijn
%A Theelen, Vera
%D 2023
%T Data underlying the research of Quality prediction of strawberries with RGB image segments
%U 
%R 10.4121/21864590.v2
%K Non-destructive analysis
%K Machine Learning approach
%K computer vision technique
%K Soft fruit
%K crop management
%K Machine Learning as a Service
%K Artificial Intelligence  and image processing
%K climate computer data
%K plant load
%K fruit quality attributes
%X <p>In this research, we validate our hypothesis of using in-field data that are acquirable via commodity hardware to obtain acceptable accuracies in predicting the quality attribute of strawberries. This dataset consists of images and segments of strawberries in the wild, their quality measurements, and climate data during cultivation.</p>
%I 4TU.ResearchData