Area of research
Plant Science · Artificial Intelligence
Research interest
Research interests include Computer science, Artificial intelligence, Feature (linguistics), Transformer, Reinforcement learning, and Relation (database).
ACF-YOLO: Feature Enhancement and Multi-Scale Alignment for Sustainable Crop Small Object Detection
A document-level relation extraction method based on dual-angle attention transfer fusion
Lightweight UAV image super-resolution method based on large-kernel attention and cross-height strategy
MKD8: An Enhanced YOLOv8 Model for High-Precision Weed Detection
GLFNet: Attention Mechanism-Based Global–Local Feature Fusion Network for Micro-Expression Recognition
MN-Net: Speech Enhancement Network via Modeling the Noise
A Reinforcement Learning-Based Generative Approach for Event Temporal Relation Extraction
A Script Event Prediction Method Based on Multi-level Joint Pretraining and Prompt Fine-Tuning
CREST-Former: A Region-Enhanced Swin Transformer for Pest Recognition Based on Contrastive Learning
AdaptPest-Net: A Task-Adaptive Network with Graph–Mamba Fusion for Multi-Scale Agricultural Pest Recognition
MCrossFormer: multi-level cross-scale transformer for photovoltaic power and lifespan prediction
A Blockchain-Based Privacy Preserving Intellectual Property Authentication Method
A Cooperative Scheduling Based on Deep Reinforcement Learning for Multi-Agricultural Machines in Emergencies
AM-MSFF: A Pest Recognition Network Based on Attention Mechanism and Multi-Scale Feature Fusion
Cotton Disease Recognition Method in Natural Environment Based on Convolutional Neural Network
HawkEye Conv-Driven YOLOv10 with Advanced Feature Pyramid Networks for Small Object Detection in UAV Imagery
A Lightweight and Dynamic Feature Aggregation Method for Cotton Field Weed Detection Based on Enhanced YOLOv8
A Topic Modeling Based on Prompt Learning
Enhanced Transformer for Remote-Sensing Image Captioning with Positional-Channel Semantic Fusion
Critical Information Mining Network: Identifying Crop Diseases in Noisy Environments
Deep hierarchical multiscale attention networks for image super-resolution
Enhancing Event Temporal Relation Extractionwith Counterfactual Reasoning and Adversarial Training