Early plant disease diagnosis is becoming more and more important. Plant diseases have an impact on a plant’s development and reduce its output. Diseases in plants can result in significant crop loss.

Deep learning has transformed anomaly detection in precision agriculture by introducing architectures that can automatically learn hierarchical representations of crop health data Han et al. (2022).

There are many deep learning approaches that have successfully supported plant pests and disease detection. In crop pest identification, deep learning methods can achieve good feature representation ...

A research team developed the Point-Line Net, a deep learning method based on the Mask R-CNN framework, ... Innovative deep learning model enhances maize phenotype detection and crop management.

Object detection using deep learning consists of ... Figure 10B demonstrates the total losses graph generated for Faster R-CNN ResNet50 by TensorBoard ... N., Lavreniuk, M., Skakun, S., and Shelestov, ...

This wiki describes how to work with object detection models trained using TensorFlow Object Detection API. OpenCV 3.4.1 or higher is required. Deep learning networks in TensorFlow are represented as ...

A research team has developed the Point-Line Net, a deep learning method based on the Mask R-CNN framework, to automatically recognize maize field images and determine the number and growth ...