Researchers have made significant progress in the field of artificial intelligence by applying deep learning techniques to automate the detection and classification of crop leaf diseases.

Researchers at The University of Osaka have developed a computer graphics (CG) model, NeuraLeaf, capable of representing a ...

Early detection of tomato leaf diseases is critical to prevent their spread, but manual detection methods for the same are time-consuming, inconsistent, and labor-intensive. To address this ...

Researchers at the University of Osaka have developed NeuraLeaf, a revolutionary CG model using deep learning to represent ...

Amanda Heemann JUNGES, Jorge Ricardo DUCATI, Cristian SCALVI LAMPUGNANI, Marcus André Kurtz ALMANÇA, Detection of grapevine leaf stripe disease symptoms by hyperspectral sensor, Phytopathologia ...

A research team led by Prof. Jiang Ni from the Institute of Genetics and Developmental Biology (IGDB) of the Chinese Academy of Sciences (CAS) proposed a cost-effective method for in-field acquisition ...

A research team showcases the application of deep learning models in identifying leaf diseases in key tropical crops such as coconut, mango, and durian, offering crucial insights for the future of ...

They focused on five common diseases that affect tomato leaves and developed a machine learning model, called PLPNet, that can accurately detect these diseases from images taken in real-time.