A5100395267- Advanced Image Fusion Techniques
- Remote-Sensing Image Classification
- Image Enhancement Techniques
- Remote Sensing and Land Use
- Urban Heat Island Mitigation
- Remote Sensing in Agriculture
- Image and Signal Denoising Methods
- Video Surveillance and Tracking Methods
- Advanced Image Processing Techniques
- Land Use and Ecosystem Services
- Advanced Neural Network Applications
- Infrared Target Detection Methodologies
- Cryospheric studies and observations
- Building Energy and Comfort Optimization
- Calibration and Measurement Techniques
- Face and Expression Recognition
- Soil Moisture and Remote Sensing
- Advanced Image and Video Retrieval Techniques
- Biometric Identification and Security
- Satellite Image Processing and Photogrammetry
- Meteorological Phenomena and Simulations
- Climate change and permafrost
- Urban Green Space and Health
- Hydrology and Watershed Management Studies
- Landslides and related hazards
Wuhan University
2016-2025
Medical Research Institute
2023
Academia Sinica
2023
Academy of Medical Sciences
2023
Chinese Academy of Medical Sciences & Peking Union Medical College
2023
Frontier Science Foundation
2023
Liechtenstein Institute
2023
John Wiley & Sons (United States)
2023
Hudson Institute
2023
Zhongnan Hospital of Wuhan University
2023
In the task of change detection (CD), high-resolution remote sensing images (HRSIs) can provide rich ground object information. However, interference from noise and complex background information also bring some challenges to CD. recent years, deep learning methods represented by convolutional neural networks (CNNs) have achieved good CD results. existing difficulty in detecting detailed objects effectively. The imbalance positive negative samples seriously affect this letter, solve above...
The task of instance segmentation in remote sensing images, aiming at performing per-pixel labeling objects the level, is great importance for various civil applications. Despite previous successes, most existing methods designed natural images encounter sharp performance degradations when they are directly applied to top-view images. Through careful analysis, we observe that challenges mainly come from lack discriminative object features due severe scale variations, low contrasts, and...
Poor weather conditions and/or sensor failure always lead to inevitable information loss for remote-sensing images acquired by passive platforms. This common issue makes the interpretation (e.g., target recognition, classification, change detection) of data more difficult. Toward this end, paper proposes reconstruct missing optical patch matching-based multitemporal group sparse representation (PM-MTGSR). In framework representation, basic idea is utilize local correlations in temporal...
The optical remote sensing images not only have to make a fundamental tradeoff between the spatial and spectral resolutions, but also are inevitable be polluted by clouds; however, existing pansharpening methods mainly focus on resolution enhancement of without cloud contamination. How fuse cloud-contaminated achieve joint removal is promising challenging work. In this paper, method for very high-resolution proposed. Furthermore, conditions practical observations with all thick clouds, thin...
Reconstruction of cloud-covered thermal infrared land surface temperature (LST) is vital for the measurement physical properties in at regional and global scales. In this paper, a novel reconstruction method Moderate Resolution Imaging Spectroradiometer (MODIS) LST data with 1-km spatial resolution proposed by combining assimilation remote sensing through nonlocality-reinforced network (NRN) model. Firstly, grading criterion introduced to evaluate importance various datasets, forming four...
Local climate zone (LCZ) mapping can explore the variability of impact urban form on thermal environment in different contexts, and large-scale LCZ help us to better understand spatial temporal dynamics areas around world. Studies have indicated that deep learning-based methods effectively perform classification. However, accuracy classification datasets is still unsatisfactory, mainly due fact traditional convolutional neural networks are not good at mining contextual information, which...
Shadows are evident in most aerial images with high resolutions, particularly urban scenes, and their existence obstructs the image interpretation following application, such as classification target detection. Most current shadow removal methods were proposed for natural images, whereas shadows remote sensing show distinct characteristics. We have therefore analyzed characteristics of this paper, we propose a new method using nonlocal (NL) operators. In method, soft is introduced to replace...
Abstract Images of outdoor scenes are usually degraded under bad weather conditions, which results in a hazy image. To date, most haze removal methods based on single image have ignored the effects sensor blur and noise. Therefore, this paper, three-stage algorithm for removal, considering noise, is proposed. In first stage, we preprocess eliminate blur/noise interference to estimate second transmission atmospheric light by dark channel prior method. third regularized method proposed recover...
Abstract Combination therapy with PD-1 blockade and IL-2 substantially improves anti-tumor efficacy comparing to monotherapy. The underlying mechanisms responsible for the synergistic effects of combination remain enigmatic. Here we show that ligation results in BATF-dependent transcriptional induction membrane-associated E3 ubiquitin ligase MARCH5, which mediates K27-linked polyubiquitination lysosomal degradation common cytokine receptor γ chain (γ c ). also activates SHP2,...
Perceptually inspired color correction methods are characterized by human visual system properties. In this paper, we propose a perceptually variational method for uneven intensity of remote sensing images. The proposed shares the same intrinsic scheme as Retinex theory, but reflectance in is solved directly within limited dynamic range and supposed to comply with gray world assumption. Considering smoothness illumination complexity reflectance, integrates L2 norm total variation prior...