The agriculture sector has an immense potential to improve the requirement of food and
supplies healthy and nutritious food. Crop insect detection is a challenging task for farmers …

This paper presents the results of the evaluation of five deep learning architectures for the
classification of soybean pest images. The performance of Inception-v3, Resnet-50, VGG-16 …

Monitoring the number of insect pests is a crucial component in pheromone-based pest
management systems. In this paper, we propose an automatic detection pipeline based on …

Presents recent significant and rapid development in the field of 2D and 3D image analysis
2D and 3D Image Analysis by Moments, is a unique compendium of moment-based image …

Entomology has had many applications in many biological domains (ie insect counting as a
biodiversity index). To meet a growing biological demand and to compensate a decreasing …

The classification of pest species in field crops, such as corn, soybeans, wheat, and canola,
is still challenging because of the tiny appearance differences among pest species. In all …

Timely and accurate identification of tea tree pests is critical for effective tea tree pest control.
We collected image data sets of eight common tea tree pests to accurately represent the true …

Classification of insect species of field crops such as corn, soybeans, wheat, and canola is
more difficult than the generic object classification because of high appearance similarity …

Abstract Integrated Pest Management (IPM) lies at the core of the current efforts to reduce
the use of deleterious chemicals in greenhouse agriculture. IPM strategies rely on the early …

Monitoring pest populations in paddy fields is important to effectively implement integrated
pest management. Light traps are widely used to monitor field pests all over the world. Most …