Area of research
Molecular Biology · Food Science
Research interest
Research focused on Compost and Visualization, with related work in PEAR, Saccharomyces cerevisiae, Maturity (psychological). Notable publications include 'A fast and easy method for predicting agricultural waste compost maturity by image-based deep learning', 'CFViSA: A comprehensive and free platform for visualization and statistics in omics-data', and 'Adaboost-Based Machine Learning Improved the Modeling Robust and Estimation Accuracy of Pear Leaf Nitrogen Concentration by In-Field VIS-NIR Spectroscopy'.
CFViSA: A comprehensive and free platform for visualization and statistics in omics-data
Adaboost-Based Machine Learning Improved the Modeling Robust and Estimation Accuracy of Pear Leaf Nitrogen Concentration by In-Field VIS-NIR Spectroscopy
A fast and easy method for predicting agricultural waste compost maturity by image-based deep learning
Genetic dissection of acetic acid tolerance in Saccharomyces cerevisiae