A research team led by Professor Takuya Yamamoto and Assistant Professor Ryusaku Matsumoto (Department of Life Science ...

By leveraging a vision foundation model called Depth Anything V2, the method can accurately segment crops across diverse environments—field, lab, and aerial—reducing both time and cost in agricultural ...

We are entering a time where machines are no longer limited to fixed commands. They are beginning to sense, learn, and ...

PUR-1 has started serving as the nation’s first reactor test bed to help the industry figure out how digital communication, ...

The evolution of farming through AI-powered crop monitoring comes with its benefits; however, there are disadvantages coupled ...

A research team has developed an advanced deep learning model, LKNet, to improve the accuracy of rice panicle counting in dense crop canopies.