A5100699817- Air Quality Monitoring and Forecasting
- Air Quality and Health Impacts
- Advanced Research in Systems and Signal Processing
- Economic and Technological Systems Analysis
- Gastric Cancer Management and Outcomes
- Image and Signal Denoising Methods
- COVID-19 diagnosis using AI
- Cell Image Analysis Techniques
- Engineering Diagnostics and Reliability
- Sparse and Compressive Sensing Techniques
- AI in cancer detection
- Anomaly Detection Techniques and Applications
- Colorectal Cancer Screening and Detection
- Energy Load and Power Forecasting
- Random lasers and scattering media
- COVID-19 impact on air quality
- Advanced Image Fusion Techniques
- Environmental Changes in China
- Advanced MRI Techniques and Applications
- Advanced Image Processing Techniques
Institute of Optics and Electronics, Chinese Academy of Sciences
2024
Harvard University
2024
Australian Centre for Robotic Vision
2024
The University of Adelaide
2024
South Australian Health and Medical Research Institute
2024
North China University of Water Resources and Electric Power
2010-2021
In recent years, the haze has caused serious troubles to people's lives, with continuous increase of PM2.5 emissions. The accurate prediction is very crucial for policy makers make predictive measures. Due nonlinearity time series, it difficult predict accurately. Despite some studies about being proposed, problem LSTM (long short-term memory) gradient disappearance and random selection wavelet orders layers isn't still solved. this study, a novel model based on WT (wavelet transform)-SAE...
Optimizing the sparse basis is an effective way to enhance single-pixel imaging performance. Compressed sensing typically employs discrete wavelet map signals into domain achieve approximate sparsity, where coefficients resemble exponential decay form. However, in penalty term of cost function, large lowfrequency carry higher weights, while weights assigned small high-frequency are much smaller. This implies that easily neglected optimization and even mistaken as noise removed, resulting...
Hallucinations in large vision-language models (LVLMs) are a significant challenge, i.e., generating objects that not presented the visual input, which impairs their reliability. Recent studies often attribute hallucinations to lack of understanding yet ignore more fundamental issue: model's inability effectively extract or decouple features. In this paper, we revisit LVLMs from an architectural perspective, investigating whether primary cause lies encoder (feature extraction) modal...
Based on the research of ecological water compensation benefit in ecology, resource, economy and society aspects, author established AHP-FCA assessment model with both analytic hierarchy process fuzzy comprehensive assessment, considering overall indicator system source areas receiving river basin. The was done, result accordance practical situation Heihe River Therefore, can be popularized.