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 of flag leaf angle (FLANG) images and developed a lightweight deep learning model, LeafPoseNet, for accurate FLANG estimation.
Deep-learning-based method enables field measurement of flag leaf angle in wheat
