22 citations · 23 across the 10 of their papers we have counts for
10 papers
Semi-Supervised Hyperbolic Hierarchical Clustering with Set-Level Structural Priors
Junjing Zheng, Xinyu Zhang, Xiangfeng Qiu +2
Semi-supervised hierarchical clustering aims to learn a tree structure consistent with data patterns and user-provided supervision. Supervision is usually given as leaf-level relat…
Mode-Aware Non-Linear Tucker Autoencoder for Tensor-based Unsupervised Learning
Junjing Zheng, Chengliang Song, Weidong Jiang +1
High-dimensional data, particularly in the form of high-order tensors, presents a major challenge in self-supervised learning. While MLP-based autoencoders (AE) are commonly employ…
SAR-GTR: Attributed Scattering Information Guided SAR Graph Transformer Recognition Algorithm
Xuying Xiong, Xinyu Zhang, Weidong Jiang +3
Utilizing electromagnetic scattering information for SAR data interpretation is currently a prominent research focus in the SAR interpretation domain. Graph Neural Networks (GNNs)…
Orientation-Aware Sparse Tensor PCA for Efficient Unsupervised Feature Selection
Junjing Zheng, Xinyu Zhang, Weidong Jiang +2
Recently, introducing Tensor Decomposition (TD) techniques into unsupervised feature selection (UFS) has been an emerging research topic. A tensor structure is beneficial for minin…
Worst-Case Riemannian Optimization with Uncertain Target Steering Vector for Slow-Time Transmit Sequence of Cognitive Radar
Xinyu Zhang, Weidong Jiang, Xiangfeng Qiu +1
Optimization of slow-time transmit sequence endows cognitive radar with the ability to suppress strong clutter in the range-Doppler domain. However, in practice, inaccurate target…
LDSF: Lightweight Dual-Stream Framework for SAR Target Recognition by Coupling Local Electromagnetic Scattering Features and Global Visual Features
Xuying Xiong, Xinyu Zhang, Weidong Jiang +1
Mainstream DNN-based SAR-ATR methods still face issues such as easy overfitting of a few training data, high computational overhead, and poor interpretability of the black-box mode…
Fast Sparse PCA via Positive Semidefinite Projection for Unsupervised Feature Selection
Junjing Zheng, Xinyu Zhang, Yongxiang Liu +3
In the field of unsupervised feature selection, sparse principal component analysis (SPCA) methods have attracted more and more attention recently. Compared to spectral-based metho…
ROFusion: Efficient Object Detection using Hybrid Point-wise Radar-Optical Fusion
Liu Liu, Shuaifeng Zhi, Zhenhua Du +4
Radars, due to their robustness to adverse weather conditions and ability to measure object motions, have served in autonomous driving and intelligent agents for years. However, Ra…
A classification performance evaluation measure considering data separability
Lingyan Xue, Xinyu Zhang, Weidong Jiang +1
Machine learning and deep learning classification models are data-driven, and the model and the data jointly determine their classification performance. It is biased to evaluate th…
Ambiguity Function Shaping based on Alternating Direction Riemannian Optimal Algorithm
Haoyu Yi, Xinyu Zhang, Weidong Jiang +1
In order to improve the ability of cognitive radar (CR) to adapt to the environment, the required ambiguity function (AF) can be synthesized by designing the waveform. The key to t…