About Me
👨🏼🌾I am Xianyu, a Ph.D student at iGE-Lab/Prof. LIU in Zhejiang University (ZJU). 🎄My study is focused on UAV, image processing, deep-learning techniques especially in Agriculture & Ecology scenes. From 2024.7, I am visiting University of Toronto (UoT) at Ensminger Lab for 1 year.
🛸I have been working on UAV image super-resolution with varianve-enhanced diffusion-model during 2023, which is promised to bridge UAV and satellite🛰️ data to achieve large-area remote sensing image refinement. 🐣In 2022, I designed a UAV image-sequence direct geo-location and trait-extraction system for real-time crop field sensing. 🔑 Now I am work on 1.Paddy field weed sensing & grading; 2.Forest tree crown instance segmentation.
🌈My future interests also include automatic few-shots learning for anomaly (pest & disease stress) region detection at crop field using UAV hyper/multi-spectral imaging, points cloud☁️ segmentation & 3D traits measurment📏 using UAV LiDAR.
Articles
Lu X, Zhang J, Yang R, et al. Effective variance attention-enhanced diffusion model for crop field aerial image super resolution. ISPRS Journal of Photogrammetry and Remote Sensing. 2024; 218:50-68. https://doi.org/10.1016/j.isprsjprs.2024.08.017
Lu X, Zhou J, Yang R, et al. Automated Rice Phenology Stage Mapping Using UAV Images and Deep Learning. Drones. 2023; 7(2):83. https://doi.org/10.3390/drones7020083
Lu X, Yang R, Zhou J, et al. A hybrid model of ghost-convolution enlightened transformer for effective diagnosis of grape leaf disease and pest. Journal of King Saud University - Computer and Information Sciences. 2022;34(5):1755-1767. https://doi.org/10.1016/j.jksuci.2022.03.006