Abstract Object Detection and Tracking have gained importance in recent years because of
the great advances in image and video analysis techniques and the accurate results these …

In the evolving landscape of precision agriculture, the integration of remote pest traps with
deep learning technologies marks a critical step forward in remote pest detection, with the …

The agricultural sector in Egypt is adversely affected by factors such as inadequate soil
fertility and environmental hazards such as pestilence and diseases. The implementation of …

Object detection for a pick-and-place system has been widely acknowledged as a significant
research area in the field of computer vision. The integration of AI and machine vision with …

With the widespread application of drone technology, the demand for pest detection and
identification from low-resolution and noisy images captured with drones has been steadily …

In recent years, the achievements of machine learning (ML) have affected all areas of
industry and it plays an increasingly important role in agriculture as well. However, for …

Codling moth (CM), Cydia pomonella, is a significant pest of apple (Malus domestica) and
other orchard crops worldwide, posing challenges due to the decrease in registered …

This paper presents an energy-optimized solution for on-device pest detection, preventing
image streaming from the traps installed in the monitored orchard surface. We optimize the …

Effective crop health monitoring is essential for farmers to make informed decisions about
managing their crops. In canola crop management, the rapid proliferation of flea beetle (FB) …

The codling moth pest poses a significant threat to global crop production, with potential
losses of up to 80% in apple orchards. Special camera-based sensor nodes are deployed in …