Raveena Selvanarayanan1, Surendran Rajendran1,*, Youseef Alotaibi2
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 759-782, 2024, DOI:10.32604/cmes.2023.044084
Abstract Colletotrichum kahawae (Coffee Berry Disease) spreads through spores that can be carried by wind, rain, and insects affecting coffee plantations, and causes 80% yield losses and poor-quality coffee beans. The deadly disease is hard to control because wind, rain, and insects carry spores. Colombian researchers utilized a deep learning system to identify CBD in coffee cherries at three growth stages and classify photographs of infected and uninfected cherries with 93% accuracy using a random forest method. If the dataset is too small and noisy, the algorithm may not learn data patterns and generate accurate predictions. To overcome the existing challenge,… More >
Login
Register
