InsectDSOT: A Neural Network for Insect Detection in Olive Trees.

: Controlling insect pests in agricultural fields is a major concern. Despite technological developments, most farm management methods and technologies still rely on experts for management and do not yet match the criteria required for precise insect pest control. In this paper, we present a neural network approach for detecting and counting insects. Using the Yolov5n 6.1 version as a baseline model, this paper proposes replacing the Conv layers in the original model’s backbone and neck with the RepVGG layer. We use transfer learning to improve performance by training our proposal on the MS COCO dataset and then use the output model of this training as the input of our new training. Our proposal is validated using the DIRT (Dacus Image Recognition Toolkit) dataset. The obtained results demonstrate that our approach, based on an improved Yolov5, achieves 86.1% of precision. It outperforms four versions of the original yolov5 and yolov5-based versions with modified backbones based on lightweight models.