Paddy seed viability prediction based on feature fusion of color and hyperspectral image with multivariate analysis
Abdullah Al Siam, M. Mirazus Salehin, Md. Shahinur Alam, Sahabuddin Ahamed, Md Hamidul Islam, Anisur Rahman
Abstract
derivative preprocessed spectra could achieve higher F1-score, recall, and precision values. The visualization map for the viable and non-viable paddy seeds was also developed utilizing the most effective predictive model. The results demonstrate the possibility of using the fusion of the hyperspectral and color image features to sort seeds according to viability, which may be applied in developing an online seed sorting method.
Topics & Concepts
Hyperspectral imagingArtificial intelligencePattern recognition (psychology)MathematicsPartial least squares regressionPreprocessorComputer scienceStatisticsSpectroscopy and Chemometric AnalysesGABA and Rice ResearchSpectroscopy Techniques in Biomedical and Chemical Research