Publications by authors named "Wei-Bo Qin"
Environ Entomol
December 2024
Article Synopsis
- The maize crop faces significant threats from four major pest species during various larval stages, making manual identification and control challenging.
- To address this, an automated system using different Convolutional Neural Network models was developed, focusing on classifying the larval stages of these pests, including the Asian corn borer and fall armyworm.
- Among the models tested, Densenet121 with the Adam optimizer achieved the highest classification accuracy of 96.65%, and performed well in real field conditions, demonstrating a 90% accuracy in identifying pest instars, highlighting its potential for improving pest management strategies in agriculture.
