Area of research
Computer Vision and Pattern Recognition · Environmental Engineering
Research interest
Research interests include Remote Sensing and LiDAR Applications, Advanced Neural Network Applications, 3D Surveying and Cultural Heritage, and 3D Shape Modeling and Analysis.
Simplify-YOLOv5m: A Simplified High-Speed Insulator Detection Algorithm for UAV Images
TFNet: point cloud Semantic Segmentation Network based on Triple feature extraction
Applying machine learning algorithms to explore the impact of combined noise and dust on hearing loss in occupationally exposed populations
Perennial sugarcane reduces soil erosion but increases N2O emissions
Mitigation of ammonia and hydrogen sulfide emissions during aerobic composting of laying hen waste through NaOH-modified biochar
EMB-YOLO: Dataset, method and benchmark for electric meter box defect detection
LCL_FDA: Local context learning and full-level decoder aggregation network for large-scale point cloud semantic segmentation
Detail R-CNN: Insulator Detection Based on Detail Feature Enhancement and Metric Learning
SS-IPLE: Semantic Segmentation of Electric Power Corridor Scene and Individual Power Line Extraction From UAV-Based Lidar Point Cloud
A Floating-Waste-Detection Method for Unmanned Surface Vehicle Based on Feature Fusion and Enhancement
InsDef: Few-Shot Learning-Based Insulator Defect Detection Algorithm With a Dual-Guide Attention Mechanism and Multiple Label Consistency Constraints
RSIn-Dataset: An UAV-Based Insulator Detection Aerial Images Dataset and Benchmark
SFL-NET: Slight Filter Learning Network for Point Cloud Semantic Segmentation
Slope planting patterns are superior to ditch grassing in reducing ditch erosion load to rivers: Evidenced from a five-year study in an intensive sugarcane growth watershed
Characteristics of Nitrogen Output during Typical Rainfall in Different Sugarcane Growth Stages in a Southern Subtropical Watershed
PTTE:Power Tower Tilt Estimation Algorithm based on LiDAR Point Cloud
MGFNet: A Progressive Multi-Granularity Learning Strategy-Based Insulator Defect Recognition Algorithm for UAV Images
Key technologies of machine vision for weeding robots: A review and benchmark
DenseKPNET: Dense Kernel Point Convolutional Neural Networks for Point Cloud Semantic Segmentation
PLE: Power Line Extraction Algorithm for UAV-Based Power Inspection
MFNet: Multi-Level Feature Extraction and Fusion Network for Large-Scale Point Cloud Classification
Control of sugarcane planting patterns on slope erosion-induced nitrogen and phosphorus loss and their export coefficients from the watershed
MSIDA-Net: Point Cloud Semantic Segmentation via Multi-Spatial Information and Dual Adaptive Blocks
AFE-RCNN: Adaptive Feature Enhancement RCNN for 3D Object Detection
Efficient 6D object pose estimation based on attentive multi‐scale contextual information
Fine root densities of grasses and perennial sugarcane significantly reduce stream channel erosion in southern China
MS-SLAM: Motion State Decision of Keyframes for UAV-Based Vision Localization
ISSD: Improved SSD for Insulator and Spacer Online Detection Based on UAV System
Sugarcane planting patterns control ephemeral gully erosion and associated nutrient losses: Evidence from hillslope observation
Vetiver grass hedgerows significantly trap P but little N from sloping land: Evidenced from a 10-year field observation