A5101499683- Infrared Target Detection Methodologies
- Cryptography and Data Security
- Soil Geostatistics and Mapping
- Speech Recognition and Synthesis
- Remote-Sensing Image Classification
- Speech and Audio Processing
- Optical Systems and Laser Technology
- Web Applications and Data Management
- Music and Audio Processing
- Complexity and Algorithms in Graphs
- Image and Video Quality Assessment
- Advanced Sensor and Control Systems
- Higher Education and Teaching Methods
- Cell Image Analysis Techniques
- Educational Technology and Assessment
- Blockchain Technology Applications and Security
- Neural Networks and Applications
- Geochemistry and Geologic Mapping
China Geological Survey
2023
Academy of Broadcasting Science
2023
Xi’an University of Posts and Telecommunications
2006-2020
Heavy metal contamination has long been a concern of intense research within the field environmental protection. The exacerbation heavy pollution due to mineral resource over-exploitation and implementation agricultural modernization further emphasized need for rapid monitoring. Although traditional geochemical survey methods have deemed reliable, they lack ability conduct non-destructive surveys large areas their high cost, low real-time capability, cumbersome operations. We collected 120...
Certificateless signcryption can simultaneously provide certificateless signature and encryption. In recent years, many schemes have been proposed. However, these are based on traditional mathematical theory not the ability of resisting quantum computing attacks. Up to now, lattice-based or encryption proposed; however, only one function cannot fulfill two functions at same time. consideration this reason, in article, a scheme from lattice (L-CLSS) is constructed. L-CLSS has three...
Recently, the ResNet-based and Transformer-based Time Delay Neural Networks (TDNN) have achieved tremendous success in area of speaker verification. However, TDNN models cannot capture global interaction information, while struggle to explore multi-scale hierarchical pyramid convolutional features. This paper proposes a novel hybrid Transformer- learn embeddings, named H-vectors, which integrates Transformer ResNet via macaron structure, fully exploiting local temporal correlations....