A5012321155- Rock Mechanics and Modeling
- Image and Signal Denoising Methods
- Tunneling and Rock Mechanics
- Pancreatitis Pathology and Treatment
- Advanced Image Processing Techniques
- Geotechnical and Geomechanical Engineering
- Image Processing Techniques and Applications
- Advanced Measurement and Detection Methods
- Advanced Data Compression Techniques
- Image and Video Quality Assessment
- Diet, Metabolism, and Disease
- Advanced Computational Techniques and Applications
- Liver Disease Diagnosis and Treatment
- Earthquake Detection and Analysis
- Advanced Vision and Imaging
- Video Surveillance and Tracking Methods
- High-Velocity Impact and Material Behavior
- Image Enhancement Techniques
- Network Traffic and Congestion Control
- Diet and metabolism studies
- Diabetes and associated disorders
- Landslides and related hazards
Chongqing University of Posts and Telecommunications
2024
Chongqing Institute of Green and Intelligent Technology
2024
Sichuan University
2013-2020
Shanghai Jiao Tong University
2004-2020
Zhejiang University of Technology
2015
This paper studies modeling approach of MPEG-4 VBR video traffic based on multifractal multiplicative model. Multiscale analysis reveals that the multiplier distribution is different in style time scales. Based statistical characteristics multipliers, a composite proposed: Gaussian used to fit at large scales, new distribution-Symmetric Pareto small scales and linear model frame traffic. Simulations are performed validate good effect this approach.
Learning-based super-resolution (SR) methods are popular in many applications recently. In these methods, the high-frequency details usually found or combined through patch matching from training database. However, representation ability of small is limited and it difficult to guarantee that super-resolved image best under global view. To this end, authors propose a statistical learning method for SR with both local constraints. More specifically, they introduce mixture model into maximum...
Deep learning has excelled in single-image super-resolution (SISR) applications, yet the lack of interpretability most deep learning-based SR networks hinders their applicability, especially fields like medical imaging that require transparent computation. To address these problems, we present an interpretable frequency division network operates image domain. It comprises a module and step-wise reconstruction method, which divides into different frequencies performs accordingly. We develop...
The elevator door protection system is one of the most important in elevator, based on image processing technology has good application prospects. Oriented to large storage capacity and strong dynamic characteristics process protection, this paper, a kind recognition brought forward. Modified median filtering method established filter noise hold boundary clearly. Otsu adopted for global threshold segmentation. Relying background subtraction temporal difference method, target identification...