1.9k citations · 2.2k across the 14 of their papers we have counts for
14 papers
DREB-Net: Dual-stream Restoration Embedding Blur-feature Fusion Network for High-mobility UAV Object Detection
Qingpeng Li, Yuxin Zhang, Leyuan Fang +3
Object detection algorithms are pivotal components of unmanned aerial vehicle (UAV) imaging systems, extensively employed in complex fields. However, images captured by high-mobili…
Deep Covariance Alignment for Domain Adaptive Remote Sensing Image Segmentation
Linshan Wu, Ming Lu, Leyuan Fang
Unsupervised domain adaptive (UDA) image segmentation has recently gained increasing attention, aiming to improve the generalization capability for transferring knowledge from the…
BSDM: Background Suppression Diffusion Model for Hyperspectral Anomaly Detection
Jitao Ma, Weiying Xie, Yunsong Li +1
Hyperspectral anomaly detection (HAD) is widely used in Earth observation and deep space exploration. A major challenge for HAD is the complex background of the input hyperspectral…
SpectralDiff: A Generative Framework for Hyperspectral Image Classification with Diffusion Models
Ning Chen, Jun Yue, Leyuan Fang +1
Hyperspectral Image (HSI) classification is an important issue in remote sensing field with extensive applications in earth science. In recent years, a large number of deep learnin…
Dif-Fusion: Towards High Color Fidelity in Infrared and Visible Image Fusion with Diffusion Models
Jun Yue, Leyuan Fang, Shaobo Xia +2
Color plays an important role in human visual perception, reflecting the spectrum of objects. However, the existing infrared and visible image fusion methods rarely explore how to…
Optical Remote Sensing Image Understanding with Weak Supervision: Concepts, Methods, and Perspectives
Jun Yue, Leyuan Fang, Pedram Ghamisi +4
In recent years, supervised learning has been widely used in various tasks of optical remote sensing image understanding, including remote sensing image classification, pixel-wise…
Peng Cheng Object Detection Benchmark for Smart City
Yaowei Wang, Zhouxin Yang, Rui Liu +4
Object detection is an algorithm that recognizes and locates the objects in the image and has a wide range of applications in the visual understanding of complex urban scenes. Exis…
NFANet: A Novel Method for Weakly Supervised Water Extraction from High-Resolution Remote Sensing Imagery
Ming Lu, Leyuan Fang, Muxing Li +3
The use of deep learning for water extraction requires precise pixel-level labels. However, it is very difficult to label high-resolution remote sensing images at the pixel level.…
LDP-Net: An Unsupervised Pansharpening Network Based on Learnable Degradation Processes
Jiahui Ni, Zhimin Shao, Zhongzhou Zhang +4
Pansharpening in remote sensing image aims at acquiring a high-resolution multispectral (HRMS) image directly by fusing a low-resolution multispectral (LRMS) image with a panchroma…
RRNet: Relational Reasoning Network with Parallel Multi-scale Attention for Salient Object Detection in Optical Remote Sensing Images
Runmin Cong, Yumo Zhang, Leyuan Fang +3
Salient object detection (SOD) for optical remote sensing images (RSIs) aims at locating and extracting visually distinctive objects/regions from the optical RSIs. Despite some sal…
Noise-Powered Disentangled Representation for Unsupervised Speckle Reduction of Optical Coherence Tomography Images
Yongqiang Huang, Wenjun Xia, Zexin Lu +5
Due to its noninvasive character, optical coherence tomography (OCT) has become a popular diagnostic method in clinical settings. However, the low-coherence interferometric imaging…
Multiscale Sparsifying Transform Learning for Image Denoising
Ashkan Abbasi, Amirhassan Monadjemi, Leyuan Fang +3
The data-driven sparse methods such as synthesis dictionary learning (e.g., K-SVD) and sparsifying transform learning have been proven effective in image denoising. However, they a…
Deep Learning for Hyperspectral Image Classification: An Overview
Shutao Li, Weiwei Song, Leyuan Fang +3
Hyperspectral image (HSI) classification has become a hot topic in the field of remote sensing. In general, the complex characteristics of hyperspectral data make the accurate clas…
Three-dimensional Optical Coherence Tomography Image Denoising through Multi-input Fully-Convolutional Networks
Ashkan Abbasi, Amirhassan Monadjemi, Leyuan Fang +2
In recent years, there has been a growing interest in applying convolutional neural networks (CNNs) to low-level vision tasks such as denoising and super-resolution. Due to the coh…