70 citations · 118 across the 6 of their papers we have counts for
7 papers
SARATR-X-v2: Scale-Aware Structural Pre-Training for SAR Foundation Models
Weijie Li, Yafei Song, Yongxiang Liu +7
Masked image modeling has become a dominant paradigm for SAR pre-training, yet the design of the reconstruction target remains fundamentally unsettled. This article argues that a S…
Machines Serve Human: A Novel Variable Human-machine Collaborative Compression Framework
Zifu Zhang, Shengxi Li, Xiancheng Sun +3
Human-machine collaborative compression has been receiving increasing research efforts for reducing image/video data, serving as the basis for both human perception and machine int…
Blind Super-Resolution via Meta-learning and Markov Chain Monte Carlo Simulation
Jingyuan Xia, Zhixiong Yang, Shengxi Li +4
Learning-based approaches have witnessed great successes in blind single image super-resolution (SISR) tasks, however, handcrafted kernel priors and learning based kernel priors ar…
A Dynamic Kernel Prior Model for Unsupervised Blind Image Super-Resolution
Zhixiong Yang, Jingyuan Xia, Shengxi Li +5
Deep learning-based methods have achieved significant successes on solving the blind super-resolution (BSR) problem. However, most of them request supervised pre-training on labell…
Towards Assessing the Synthetic-to-Measured Adversarial Vulnerability of SAR ATR
Bowen Peng, Bo Peng, Jingyuan Xia +3
Recently, there has been increasing concern about the vulnerability of deep neural network (DNN)-based synthetic aperture radar (SAR) automatic target recognition (ATR) to adversar…
A Meta-Learning Based Gradient Descent Algorithm for MU-MIMO Beamforming
Jing-Yuan Xia, Zhixiong Yang, Tong Qiu +2
Multi-user multiple-input multiple-output (MU-MIMO) beamforming design is typically formulated as a non-convex weighted sum rate (WSR) maximization problem that is known to be NP-h…
A Learning Aided Flexible Gradient Descent Approach to MISO Beamforming
Zhixiong Yang, Jing-Yuan Xia, Junshan Luo +2
This paper proposes a learning aided gradient descent (LAGD) algorithm to solve the weighted sum rate (WSR) maximization problem for multiple-input single-output (MISO) beamforming…