A5048750798- Advanced SAR Imaging Techniques
- Synthetic Aperture Radar (SAR) Applications and Techniques
- Geophysical Methods and Applications
- Advanced Neural Network Applications
- Mesenchymal stem cell research
- Algorithms and Data Compression
- Heavy metals in environment
- Advanced Image and Video Retrieval Techniques
- Structural Analysis and Optimization
- Maritime and Coastal Archaeology
- Infrared Target Detection Methodologies
- Geochemistry and Elemental Analysis
- Antenna Design and Optimization
- 3D Printing in Biomedical Research
- Traffic Prediction and Management Techniques
- Osteoarthritis Treatment and Mechanisms
- Advanced Data Compression Techniques
- Laser and Thermal Forming Techniques
- Qualitative Comparative Analysis Research
- Autonomous Vehicle Technology and Safety
- Mercury impact and mitigation studies
Aerospace Information Research Institute
2021-2025
China Geological Survey
2025
University of Chinese Academy of Sciences
2023-2024
Chinese Academy of Sciences
2023-2024
Shanghai Industrial Technology Institute
2024
Beijing Jiaotong University
2023
University of Science and Technology of China
2023
Soochow University
2023
First Affiliated Hospital of Soochow University
2023
Shanghai Innovative Research Center of Traditional Chinese Medicine
2012
Reconstruction of osteochondral (OC) defects represents an immense challenge due to the need for synchronous regeneration special stratified tissues. The revolutionary innovation bioprinting provides a robust method precise fabrication tissue-engineered OCs with hierarchical structure; however, their spatial living cues simultaneous fulfilment osteogenesis and chondrogenesis reconstruct cartilage-bone interface OC are underappreciated. Here, inspired by natural bilayer features, anisotropic...
Ship detection in synthetic aperture radar (SAR) images has attracted widespread attention due to its significance and challenges. In recent years, numerous detectors based on deep learning have achieved good performance the field of SAR ship detection. However, targets same type always various representations under different imaging conditions, while types ships may a high degree similarity, which considerably complicates target recognition. Meanwhile, image is also obscured by background...
Deep learning has been widely used in the field of SAR ship detection. However, current detection still faces many challenges, such as complex scenes, multiple scales, and small targets. In order to promote solution above problems, this article releases a high-resolution dataset which can be for rotating frame target The contains six categories ships. total, 30 panoramic tiles Chinese Gaofen-3 port areas with 1-m resolution were cropped slices, each 1024 × pixels. addition, most images...
The contamination of marine ecosystems with metal(loid)s is an increasing environmental concern, largely driven by anthropogenic activities, and poses a significant risk to the health human well-being. Geochemical background values represent typical concentrations trace elements observed in natural environment. utilization disparate gives rise evaluation outcomes. objective this study was investigate concentration profiles (Cu, Pb, Zn, Cr, Cd, As, Hg) along sediment core order obtain assess...
Synthetic Aperture Radar (SAR) ship target detection has been extensively researched. However, most methods use the same dataset division for both training and validation. In practical applications, it is often necessary to quickly adapt new loads, modes, data detect targets effectively. This presents a cross-domain problem that requires further study. paper proposes method detecting SAR ships in complex backgrounds using fusion tensor adversarial learning. The designed address of with large...
Synthetic aperture radar (SAR) has emerged as a critical technology for detecting and classifying objects such ships in challenging environments. However, few-shot learning remains due to the limited availability of labeled SAR data, complex backscatter, variations imaging parameters. In this paper, we propose novel network, scattering point topology ship classification (SPT-FSC), which addresses these challenges by incorporating characteristics into network process through (SPT) based on...
Texture compression is an important technique widely adopted in graphics processing units (GPUs) nowadays to reduce memory bandwidth consumption. However, modern texture schemes cannot generate satisfactory visual qualities for both alpha channel and color of images. In this paper we present a novel scheme, called CATC (Complexity-Aware Compression), based on the insight into essential differences between transparency color. defines new data formats compresses image flexibly. employs...
A sustainable training system for acupuncture-moxibustion and
Abstract This article adopts a modular design concept to an active phased array radar antenna system structure and elaborates on its structural layout thermal content. A finite element model of the framework was established, rationality verified through static simulation analysis.
Deep learning has achieved remarkable results in the field of target detection and recognition. For small targets images, image pyramid can be used to fuse multi-scale features improve performance. However, when test on remote sensing it is found that some important goals will still missed. Aiming at problems this paper proposes two S2ANet improved network variants based attention mechanism for synthetic aperture radar(SAR) payload optical payload: SAR CBAM(Convolutional Block Attention...
<p>Synthetic Aperture Radar (SAR) has emerged as a critical technology for detecting and classifying objects such ships in challenging environments. However, few-shot learning remains challenge due to the limited availability of labeled SAR data, complex radar backscatter, variations imaging parameters. In this paper, we propose novel network, Scattering Point Topology Few-Shot Ship Classification (SPT-FSC), which addresses these challenges by incorporating scattering characteristics...
<p>Synthetic Aperture Radar (SAR) has emerged as a critical technology for detecting and classifying objects such ships in challenging environments. However, few-shot learning remains challenge due to the limited availability of labeled SAR data, complex radar backscatter, variations imaging parameters. In this paper, we propose novel network, Scattering Point Topology Few-Shot Ship Classification (SPT-FSC), which addresses these challenges by incorporating scattering characteristics...