A5060297459- Advanced Graph Neural Networks
- Radar Systems and Signal Processing
- Advanced SAR Imaging Techniques
- Complex Network Analysis Techniques
- Machine Learning in Bioinformatics
- Metallurgy and Material Forming
- Wireless Signal Modulation Classification
- Anomaly Detection Techniques and Applications
- Graph Theory and Algorithms
- Microstructure and Mechanical Properties of Steels
- Metal Forming Simulation Techniques
- Machine Learning and Algorithms
China Jiliang University
2023-2024
Dongfeng Motor Group (China)
2023
The primary challenge of multi-label active learning, differing it from multi-class lies in assessing the informativeness an indefinite number labels while also accounting for inherited label correlation. Existing studies either require substantial computational resources to leverage correlations or fail fully explore dependencies. Additionally, real-world scenarios often addressing intrinsic biases stemming imbalanced data distributions. In this paper, we propose a new learning strategy...
Radar signal recognition under low signal-to-noise ratio (SNR) conditions is a critical issue in modern electronic reconnaissance systems, which face significant challenges accuracy due to diversity. A novel method for radar detection based on the bagging support vector machine (SVM) proposed this paper.This firstly utilizes Choi–Williams distribution (CWD) and smooth pseudo Wigner-Ville (SPWVD) obtain different time–frequency images of signals, effectively leverages CWD’s strong aggregation...