About this Research Topic
This research topic aims to explore recent advanced AI methods for plant disease and pest recognition for real-world applications. We welcome submissions of all article types published in Frontiers in Plant Science. Studies of interest cover the following but are not limited to:
• High-quality datasets.
• Multi-modal sensor, including RGB, video, multi-spectral, and depth images, and the internet of things (IoT).
• Learning with multi-crop and multi-dataset.
• Foundation models and their applications.
• Small deep-learning models with limited resources.
• Data-centric methods, such as learning from noisy and unlabeled data, data augmentation, open set recognition, and domain generalization.
• Applications, including classification, detection, and segmentation.
• Early plant disease and pest recognition.
• Quantitative evaluation of the plants infected by diseases and pests.
• Incidence analysis.
• Information security for plant disease and pest recognition.
• Cloud and edge computing.
• Real-world application and robotic system development.
• Cell division of disease-infected plants.
Keywords: plant disease, pest recognition, artificial intelligence, deep learning
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.