A5101683469- Advanced Image Fusion Techniques
- Brain Tumor Detection and Classification
- Image and Signal Denoising Methods
- Image Enhancement Techniques
- Image Processing Techniques and Applications
- Chaos-based Image/Signal Encryption
- Advanced Neural Network Applications
- Industrial Vision Systems and Defect Detection
- Remote-Sensing Image Classification
- Video Surveillance and Tracking Methods
- CCD and CMOS Imaging Sensors
- Quantum chaos and dynamical systems
- Advanced Image Processing Techniques
- AI in cancer detection
- Generative Adversarial Networks and Image Synthesis
- Radiomics and Machine Learning in Medical Imaging
- Advanced Memory and Neural Computing
- Chaos control and synchronization
- Medical Imaging Techniques and Applications
- Visual Attention and Saliency Detection
- Advanced Steganography and Watermarking Techniques
- Neural dynamics and brain function
- Photoacoustic and Ultrasonic Imaging
- Infrared Thermography in Medicine
- Digital Radiography and Breast Imaging
Lanzhou Jiaotong University
2018-2025
Dalian University of Technology
2022-2024
Lanzhou University
2013-2024
Tsinghua–Berkeley Shenzhen Institute
2024
Tsinghua University
2024
Shanghai University of Engineering Science
2024
Guangxi University
2024
Guangxi University of Chinese Medicine
2024
C-Com Satellite Systems (Canada)
2023
University of Washington
1992
Exploring and establishing artificial neural networks with electrophysiological characteristics high computational efficiency is a popular topic in the field of computer vision. Inspired by working mechanism primary visual cortex, pulse-coupled network (PCNN) can exhibit synchronous oscillation, refractory period, exponential decay. However, evidence shows that neurons highly complex non-linear dynamics when stimulated external periodic signals. This chaos phenomenon, also known as "...
Specific emitter identification (SEI) is a technique that identifies the through physical layer features contained in radio signals, and it widely used tasks such as identifying illegal transmitters authentication. Thanks to development of deep learning, SEI based on learning have achieved significant improvements recognition performance. However, often broadcast for short durations at low frequencies, resulting very limited available training samples. In cases, directly models may lead...
ABSTRACT Bearings are a critical part of various industrial equipment. Existing bearing fault detection methods face challenges such as complicated data preprocessing, difficulty in analysing time series data, and inability to learn multi‐dimensional features, resulting insufficient accuracy. To address these issues, this study proposes novel diagnosis model called multi‐channel deep pulse‐coupled net (MC‐DPCN) inspired by the mechanisms image processing primary visual cortex brain....
The task of the detection unmanned aerial vehicles (UAVs) is great significance to social communication security. Infrared technology has advantage not being interfered with by environmental and other factors can detect UAVs in complex environments. Since infrared equipment expensive data collection difficult, there are few existing UAV-based images, making it difficult train deep neural networks; addition, background clutter noise such as heavy clouds, buildings, etc. signal-to-clutter...
Abstract The phenomenon of semantic satiation, which refers to the loss meaning a word or phrase after being repeated many times, is well-known psychological phenomenon. However, microscopic neural computational principles responsible for these mechanisms remain unknown. In this study, we use deep learning model continuous coupled networks investigate mechanism underlying satiation and precisely describe process with neuronal components. Our results suggest that, from mesoscopic perspective,...