Efficient Detection of Invasive Stink Bugs Using Convolutional Neural Networks

Timely pest detection and identification is critical as part of modern agriculture. Halyomorpha Halys is a prevalent pest with proven harmful impacts on numerous crops and agricultural regions. The paper proposes an efficient model to improve the detection of two invasive stink bugs: Halyomorpha halys and Nezara Viridula. Automatic detection of these two bugs is essential in various fields, such as precision agriculture and integrated pest management. The high performances obtained in the present study open new perspectives for the further development of insect pest detection systems and can serve as a basis for future modifications and improvements of these models.