A5034678630- Remote Sensing in Agriculture
- Advanced Image Fusion Techniques
- Remote-Sensing Image Classification
- Remote Sensing and LiDAR Applications
- Flood Risk Assessment and Management
- Land Use and Ecosystem Services
- Hydrology and Watershed Management Studies
- Traffic Prediction and Management Techniques
- Advanced Sensor and Energy Harvesting Materials
- Advanced Image Processing Techniques
- Network Security and Intrusion Detection
- Remote Sensing and Land Use
- Advanced Photocatalysis Techniques
- Advanced biosensing and bioanalysis techniques
- Advanced Malware Detection Techniques
- Conducting polymers and applications
- Surface Modification and Superhydrophobicity
- Biosensors and Analytical Detection
- Perovskite Materials and Applications
- Anomaly Detection Techniques and Applications
- Automated Road and Building Extraction
- Music and Audio Processing
- Network Traffic and Congestion Control
- Geochemistry and Geologic Mapping
- Autonomous Vehicle Technology and Safety
Chinese Academy of Sciences
2016-2025
Wuhan Institute of Physics and Mathematics
2020-2025
Zhejiang Provincial People's Hospital
2025
Huazhong University of Science and Technology
2015-2025
Peking University
2014-2024
Hangzhou Dianzi University
2024
South China Agricultural University
2023-2024
Dalian Polytechnic University
2024
Nantong University
2024
Hubei University
2024
Monitoring open water bodies accurately is an important and basic application in remote sensing. Various body mapping approaches have been developed to extract from multispectral images. The method based on the spectral index, especially Modified Normalized Difference Water Index (MDNWI) calculated green Shortwave-Infrared (SWIR) bands, one of most popular methods. recently launched Sentinel-2 satellite can provide fine spatial resolution This new dataset potentially significance for...
Typical organic photovoltaic materials show high Urbach energies (ca. 25–50 meV), which is considerably higher than those of their inorganic counterparts and limits further improvement in the device efficiency solar cells (OSCs). In this study, we introduce a facile method selenium substitution to reduce energy 20.4 meV (Y6Se), lowest value reported for high-performance very close 15 meV) typical inorganic/hybrid semiconductors, such as crystalline silicon, gallium nitride, lead-halide...
Sentinel-2 is a wide-swath and fine spatial resolution satellite imaging mission designed for data continuity enhancement of the Landsat other missions. The are freely available at global scale, have similar wavelengths same geographic coordinate system as data, which provides an excellent opportunity to fuse these two types sensor together. In this paper, new approach presented fusion 8 Operational Land Imager Multispectral their resolutions continuous monitoring. 30 m bands downscaled 10...
Despite the high-efficiency and low-cost prospect for perovskite solar cells, great concerns of lead toxicity instability remain this technology. Here, we report an encapsulation strategy modules based on lead-adsorbing ionogel, which prevents leakage withstand long-term stability tests. The ionogel layers integrated both sides enhance impact resistance. self-healable can prevent water permeation into layer adsorb that might leak. encapsulated devices pass damp heat thermal cycling...
Abstract River wetted width (RWW) is an important variable in the study of river hydrological and biogeochemical processes. Presently, RWW often measured from remotely sensed imagery, accuracy estimation typically low when coarse spatial resolution imagery used because boundaries run through pixels that represent a region mixture water land. Thus, conventional hard classification methods are RWW, mixed pixel problem can become large source error. To address this problem, paper proposes novel...
Super-resolution mapping (SRM) is a technique to produce land cover map with finer spatial resolution by using fractional proportion images as input. A two-step SRM approach has been widely used. First, fine-resolution indicator estimated for each class from the coarse-resolution image. All maps are then combined create final map. In this letter, three popular interpolation methods, Inverse Distance Weighted (IDW), Spline and Kriging, well four combination strategies, including maximal value...
Monitoring the spatiotemporal dynamics of surface water from remote sensing imagery is essential for understanding water's impact on global ecosystem and climate change. There often a tradeoff between spatial temporal resolutions acquired current satellite sensors as such various image fusion methods have been explored to circumvent challenges this situation presents (e.g., STARFM). However, some persist in mapping at desired fine resolution. Principally, changes bodies are abrupt controlled...
Soil organic carbon (SOC) is the largest pool and a key property of ecosystems. Compared with traditional field surveys, remote sensing (RS) represents more efficient approach to mapping SOC, especially in larger-scale areas. Hyperspectral imagery provides great potential for SOC prediction, but predicting content at regional scale given year remains challenge. Multispectral RS images (e.g., Landsat images) middle spatial resolution can be used as an alternative predict amongst other images....
The limitations of autologous bone grafts necessitate the development advanced biomimetic biomaterials for efficient cranial defect restoration. bones are typical flat with sandwich structures, consisting a diploe in middle region and 2 outer compact tables. In this study, we originally developed types flat-bone-mimetic β-tricalcium phosphate bioceramic scaffolds (Gyr-Comp Gyr-Tub) by high-precision vat-photopolymerization-based 3-dimensional printing. Both had layers an inner layer gyroid...
Super-resolution mapping (SRM) is a promising technique to generate fine resolution land cover map from coarse fractional images by predicting the spatial locations of different classes at subpixel scale. In most cases, SRM accomplished using dependence principle, which simple method describe patterns classes. However, principle used in existing models does not fully reflect real-world situations, making resultant often have uncertainty. this paper, an example-based model support vector...
Spatio-temporal fusion of MODIS and Landsat data aims to produce new that have simultaneously the spatial resolution temporal resolution. It is an ill-posed problem involving large uncertainty, especially for reproduction abrupt changes heterogeneous landscapes. In this paper, we proposed incorporate freely available 250 m images into spatio-temporal increase prediction accuracy. The bands 1 2 are fused with 500 3-7 using advanced area-to-point regression kriging approach. Based on a...
It has been demonstrated that the deregulation of microRNAs (miRNAs) affects development rheumatoid arthritis (RA). The primary objective current study was to determine role miR-143-3p in progression RA. expression synovium taken from patients with RA assessed by reverse transcription-quantitative polymerase chain reaction. higher tissues than osteoarthritis (OA). decreased suppressed cell proliferation and promoted apoptosis vitro. In addition, inhibition levels inflammatory cytokines, as...
Dams play a significant role in altering the spatial pattern of temperature rivers and contribute to thermal pollution, which greatly affects river aquatic ecosystems. Understanding temporal variation pollution caused by dams is important prevent or mitigate its harmful effect. Assessments based on in-situ measurements are often limited practice because inaccessibility water records scarcity gauges along rivers. By contrast, infrared remote sensing provides an alternative approach monitor...
Detailed information on the spatial-temporal change of impervious surfaces is important for quantifying effects rapid urbanization. Free access Landsat archive provides new opportunities surface mapping with fine spatial and temporal resolution. To improve classification accuracy, a consistency (TC) model may be applied original results time-series datasets. However, existing TC models only use class labels, ignore uncertainty during process. In this study, an uncertainty-based (USTC) was...
Road safety for automated vehicles requires accurate and early detection of stationary objects in the vehicle's path. Radar can use doppler to effectively identify make these identifications at long range severe weather poor light conditions. In this paper, we propose a radar-based object system that combines signal processing techniques with machine learning technology detect in-path from low level spectra front looking radars. The proposed consists novel image methods extract key features...
Fine-tuning is a key approach for adapting language models to specific downstream tasks, but updating all model parameters becomes impractical as sizes increase. Parameter-Efficient Fine-Tuning (PEFT) methods, such Low-Rank Adaptation (LoRA), address this challenge by introducing additional adaptation into pre-trained weight matrices. However, LoRA's performance varies across different insertion points within the model, highlighting potential parameter inefficiency due unnecessary...