A5100366744- Synthetic Aperture Radar (SAR) Applications and Techniques
- Sparse and Compressive Sensing Techniques
- Microwave Imaging and Scattering Analysis
- Advanced SAR Imaging Techniques
- Blind Source Separation Techniques
- Atmospheric Ozone and Climate
- Animal Behavior and Welfare Studies
- Landslides and related hazards
- Forest Insect Ecology and Management
- Remote Sensing in Agriculture
- Remote Sensing and Land Use
- Advanced Data Compression Techniques
- Geological and Geochemical Analysis
- Plant Pathogens and Fungal Diseases
- Hydrology and Watershed Management Studies
- Plant Pathogens and Resistance
- Geophysical Methods and Applications
- Air Quality and Health Impacts
- Karst Systems and Hydrogeology
- Infrared Thermography in Medicine
- Species Distribution and Climate Change
- Lattice Boltzmann Simulation Studies
- Insect Pheromone Research and Control
- Enhanced Oil Recovery Techniques
- Full-Duplex Wireless Communications
Chinese Academy of Sciences
2010-2024
University of Chinese Academy of Sciences
2010-2024
Aerospace Information Research Institute
2020-2024
Institute of Oceanology
2023
State Key Laboratory of Remote Sensing Science
2022
Los Alamos National Laboratory
2021
Northwest Institute of Eco-Environment and Resources
2020
University of California, Los Angeles
2019
National Computer Network Emergency Response Technical Team/Coordination Center of Chinar
2016
Zhanjiang Experimental Station
2012-2015
Monitoring animal activities help assess the effects of environmental conditions and anthropogenic factors on various species. Entomology-related monitoring methods based radar, machine vision, other technologies have developed rapidly in recent years. This research focuses real-time, laser-based that enable online insect activity study response populations to changes such as weather. We summarise four specific applications insects laser remote sensing techniques, including setting...
The fractional cover of vegetation (PV) and exposed bedrock are key ecological indicators the extent degree land degradation in karst regions. In this study, we suggested compared new methodology for direct objective estimation rocky desertification with hyperspectral multispectral imagery. results showed that Hyperion estimated covers PV had good correlation field surveyed R2 (coefficient determination) RMSE (root mean square error) was 0.91 0.05, respectively; while not so good, 0.53 0.11,...
Although current proposed compression schemes achieve better performance than traditional data schemes, they have not fully exploited the spatial and temporal correlations among data, design of projection (measurement) matrix cannot satisfy requirement real scenarios adaptively. Hence, well-designed clustering algorithm is needed to further explore strong correlation, an adaptive measurement also ensure exact recovery. In this paper, we propose a fog-based optimized Kronecker-supported...
Remote sensing technology provides a feasible option for early prediction wheat Fusarium head blight (FHB). This study presents methodology the dynamic of this classic meteorological crop disease. Host and habitat conditions were comprehensively considered as inputs FHB model, advantages, accuracy, generalization ability model evaluated. Firstly, multi-source satellite images used to predict growth stages obtain remote features, then weather features around predicted extracted. Then, with...
Composite regularization models are widely used in sparse signal processing, making multiple pa-rameters selection a significant problem to be solved. Variety kinds of composite microwave imaging, including ℓ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> and xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> penalty, nonconvex TV combined dictionary, etc. In this article, new adaptive parameters method named L-hypersurface is proposed....
Low-cost uncooled infrared thermal cameras show a large application potential for the rapid diagnosis of pig diseases. However, with increase in ambient temperature and absorbing radiation, almost all them produce severe drift provide poor accuracy measurement. In addition, unknown surface emissivity on pig’s body can also bring measuring errors. this article, an camera 3°C was used to develop smartphone-based sensor temperature. Based sensor, we proposed system combined internal calibration...
Abstract Tomographic synthetic aperture radar is an advanced multi‐channel interferometric technique for retrieving 3‐D spatial information. It can be regarded as inherently sparse reconstruction problem and solved using compressive sensing algorithms. However, the performances are limited by number of acquisitions suffer from computational burdens in practice. This paper proposes a novel method based on deep learning, which carried out optimized end‐to‐end manner generative adversarial...
Training high-quality deep models necessitates vast amounts of data, resulting in overwhelming computational and memory demands. Recently, data pruning, distillation, coreset selection have been developed to streamline volume by retaining, synthesizing, or selecting a small yet informative subset from the full set. Among these methods, pruning incurs least additional training cost offers most practical acceleration benefits. However, it is vulnerable, often suffering significant performance...
In this paper, we investigate the problem of recovering positive semi-definite (PSD) matrix from 1-bit sensing. The measurement is rank-1 and constructed by outer product a pair vectors, whose entries are independent identically distributed (i.i.d.) Gaussian variables. recovery solved in closed form through convex programming. Our analysis reveals that solution biased general. However, case error-free measurement, find for rank-r PSD with bounded condition number, bias decreases an order...