(untitled) (International Journal of Food and Nutritional Sciences, 2023)
Traditional multispectral image classification has relied on static learning with assumptions about stochastic input data. Challenges such as spatial and dynamic data sources, temporal anomalies, and spectral dissimilarities in both online and time-series multispectral image processing can lead to reduced classification accuracy or render the data useless.