An automatic diagnosis system based on wearable augmented reality (AR) glasses and an artificial intelligence (AI)model was developed to assess leafminer damage levels, and it achieved 92.38% accuracy. The DeepLab-Leafminer model incorporated an edge-aware module and the Canny loss function into the DeepLabv3+ model, which enhanced its ability to segment the leafminer damaged area in leaves.A mobile application and a web platform were developed to display the diagnostic results of leafminer damage levels for surveyors to guide their scientific decisions for leafminer prevention and control.

A research paper by scientists at The Chinese University of Hong Kong proposed a 3D radar-based control scheme that realizes the navigated locomotion of microswimmers in 3D space with multiple static and dynamic obstacles.

The new research paper, published on Jun. 2 in the journal Cyborg and Bionic Systems, presented a 3D hierarchical radar with a motion sphere and a detection sphere is firstly developed. Using the radar-based avoidance approach, the desired motion direction for the microswimmer to avoid obstacles can be obtained, and the coarse-to-fine search is used to decrease the computational load of the algorithm. Three navigation modes of the microswimmer in 3D space with dynamic conditions are realized by the radar-based navigation strategy that combines the global path planning algorithm and the radar-based avoidance approach.