Saud Yonbawi1, Sultan Alahmari2, T. Satyanarayana murthy3, Ravuri Daniel4, E. Laxmi Lydia5, Mohamad Khairi Ishak6, Hend Khalid Alkahtani7,*, Ayman Aljarbouh8, Samih M. Mostafa9
Computer Systems Science and Engineering, Vol.46, No.3, pp. 3847-3864, 2023, DOI:10.32604/csse.2023.036552
Abstract Crop insect detection becomes a tedious process for agronomists because a substantial part of the crops is damaged, and due to the pest attacks, the quality is degraded. They are the major reason behind crop quality degradation and diminished crop productivity. Hence, accurate pest detection is essential to guarantee safety and crop quality. Conventional identification of insects necessitates highly trained taxonomists to detect insects precisely based on morphological features. Lately, some progress has been made in agriculture by employing machine learning (ML) to classify and detect pests. This study introduces a Modified Metaheuristics with Transfer Learning based Insect Pest Classification… More >
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