A5100635716- Sparse and Compressive Sensing Techniques
- Cognitive Radio Networks and Spectrum Sensing
- Advanced MIMO Systems Optimization
- Blind Source Separation Techniques
- Advanced Adaptive Filtering Techniques
- Microwave Imaging and Scattering Analysis
- Age of Information Optimization
- Traffic Prediction and Management Techniques
- Advanced Photocatalysis Techniques
- Remote Sensing in Agriculture
- Copper-based nanomaterials and applications
- Satellite Communication Systems
- Remote Sensing and Land Use
- Traffic and Road Safety
- Advanced Image Fusion Techniques
- Indoor and Outdoor Localization Technologies
- Olfactory and Sensory Function Studies
- Remote Sensing and LiDAR Applications
- Biochemical Analysis and Sensing Techniques
- Image and Signal Denoising Methods
- Traffic control and management
- Solar-Powered Water Purification Methods
- Autonomous Vehicle Technology and Safety
- Stock Market Forecasting Methods
- Catalytic Processes in Materials Science
China University of Geosciences (Beijing)
2024-2025
Harbin Institute of Technology
2022-2025
National University of Singapore
2025
Centre for Quantum Technologies
2025
State Key Laboratory of Remote Sensing Science
2024
Nanyang Normal University
2023-2024
Macau University of Science and Technology
2024
Wuhan University
2023-2024
University of Maryland, College Park
2024
State Grid Corporation of China (China)
2024
Deepfakes allow for the automatic generation and creation of (fake) video content, e.g. through generative adversarial networks. Deepfake technology is a controversial with many wide reaching issues impacting society, election biasing. Much research has been devoted to developing detection methods reduce potential negative impact deepfakes. Application neural networks deep learning one approach. In this paper, we consider deepfake technologies Xception MobileNet as two approaches...
Abstract Single photon sources (SPSs) are directly applicable in quantum key distribution (QKD) because they allow the implementation of canonical BB84 protocol. To date, QKD implementations using SPS not widespread need for cryogenic operation, or frequency conversion to a wavelength efficiently transmitted over telecommunication fibers. We report an observation polarization-encoded room-temperature telecom based on GaN defect. A field test 3.5 km deployed fiber with 4.0 dB loss yielded...
The increasing number of Internet Things (IoT) objects has been a growing challenge the current spectrum supply. To handle this issue, IoT devices should have cognitive capabilities to access unoccupied portion wideband spectrum. However, most are difficult perform sensing using either conventional Nyquist sampling system or sub-Nyquist since both power-hungry components and intricate hardware unrealistic in power-constrained paradigm. In paper, we propose blind joint scheme by utilizing...
Wideband spectrum sensing is regarded as one of the key functional blocks in cognitive radio systems, where compressive (CS) has become promising techniques to deal with Nyquist sampling rate bottleneck. Theoretical analyses and simulations have shown that CS could achieve both high detection low false alarm probabilities wideband sensing. However, implementation over real-world signals real-time processing poses significant challenges due computational burden reconstruction errors against...
The application of AI large models in image processing technology is continuously expanding and deepening. They automatically extract feature information from raw data through deep learning perform efficient analysis processing. This article provides a review the current state technology, focusing on techniques based machine models. It found that introduction has led to more rapid intelligent development technology.
As an important component of terrestrial ecosystems, mountain vegetation serves as indicator climate change. Due to the sensitivity Tibetan Plateau Mountains (TPM) change and their ecological fragility, dynamics (greenness greening) have become a hot spot issue in global environmental Topography is relatively stable factor that shapes by creating localized microenvironments. However, existing research primarily focuses on effects human activities dynamics. Therefore, more comprehensive...
This paper proposes a new spectrum sensing technique, referred to as autonomous compressive (CS)-augmented sensing, which can be developed provide more efficient opportunity identification than geolocation database methods. First, we propose an CS-based algorithm that enables the local secondary users (SUs) automatically choose minimum time without knowledge of spectral sparsity or channel characteristics. The samples are collected block-by-block in time, while is gradually reconstructed...
Monitoring vegetation dynamics (VD) is crucial for environmental protection, climate change research, and understanding carbon water cycles. Remote sensing an effective method large-scale long-term VD monitoring, but it faces challenges due to changing data uncertainties caused by various factors, including observational conditions. Previous studies have demonstrated the significance of implementing proper quality control (QC) remote accurate monitoring. However, impact different QC methods...