Area of research
Computer Vision and Pattern Recognition · Signal Processing
Research interest
Research interests include Computer science, Artificial intelligence, Computer vision, Residual, Regularization (linguistics), and Feature (linguistics).
UECNet: A unified framework for exposure correction utilizing region-level prompts
CSFIN: A lightweight network for camouflaged object detection via cross-stage feature interaction
Multi-scale wavelet feature fusion network for low-light image enhancement
Conditional Laplacian pyramid networks for exposure correction
Prompt-Based Two-Stage Enhancement for Low-Light Object Detection
FD-Net: Feature Distillation Network for Oral Squamous Cell Carcinoma Lymph Node Segmentation in Hyperspectral Imagery
PRNet: Pyramid Restoration Network for RAW Image Super-Resolution
DSCA-PSPNet: Dynamic spatial-channel attention pyramid scene parsing network for sugarcane field segmentation in satellite imagery
Object detection on low-resolution images with two-stage enhancement
Illumination-aware divide-and-conquer network for improperly-exposed image enhancement
Joint Image and Feature Enhancement for Object Detection under Adverse Weather Conditions
Tunable collective electromagnetic induced transparency-like effect due to coupling of dual-band bound states in the continuum
Auxiliary Domain-Guided Adaptive Object Detection in Adverse Weather Conditions
Joint Image Super-Resolution and Low-Light Enhancement in the Dark
DENet: Detection-driven Enhancement Network for Object Detection Under Adverse Weather Conditions
Hyperspectral pathology image classification using dimension-driven multi-path attention residual network
Multi-scale feature selection network for lightweight image super-resolution
DLEN: Deep Laplacian Enhancement Networks for Low-Light Images
BMISP: Bidirectional mapping of image signal processing pipeline
PCMG:3D point cloud human motion generation based on self-attention and transformer
A Two-Stage Convolutional Neural Network for Joint Demosaicking and Super-Resolution
Accurate single image super-resolution using multi-path wide-activated residual network
Data-adaptive low-rank modeling and external gradient prior for single image super-resolution
Single Image Super Resolution Using Joint Regularization
Single image super-resolution using collaborative representation and non-local self-similarity
Multi-operator Image Retargeting with Preserving Aspect Ratio of Important Contents
Convex dictionary learning for single image super-resolution
Compressive Sensing Reconstruction of Correlated Images Using Joint Regularization
N-port strictly non-blocking optical router based on Mach-Zehnder optical switch for photonic networks-on-chip
Color image compressive sensing reconstruction by using inter-channel correlation