Publications (27)
p Norm Constraint Leaky LMS Algorithm for Sparse System Identification
Yong Feng, Rui Zeng, Jiasong Wu
This paper proposes a new leaky least mean square (leaky LMS, LLMS) algorithm in which a norm penalty is introduced to force the solution to be sparse in the application of system…
p-norm-like Constraint Leaky LMS Algorithm for Sparse System Identification
Yong Feng, Rui Zeng, Jiasong Wu
In this paper, we propose a novel leaky least mean square (leaky LMS, LLMS) algorithm which employs a p-norm-like constraint to force the solution to be sparse in the application o…
Deep Learning for Hybrid Beamforming with Finite Feedback in GSM Aided mmWave MIMO Systems
Zhilin Lu, Xudong Zhang, Rui Zeng +1
Hybrid beamforming is widely recognized as an important technique for millimeter wave (mmWave) multiple input multiple output (MIMO) systems. Generalized spatial modulation (GSM) i…
Color Image Classification via Quaternion Principal Component Analysis Network
Rui Zeng, Jiasong Wu, Zhuhong Shao +3
The Principal Component Analysis Network (PCANet), which is one of the recently proposed deep learning architectures, achieves the state-of-the-art classification accuracy in vario…
Kernel principal component analysis network for image classification
Dan Wu, Jiasong Wu, Rui Zeng +3
In order to classify the nonlinear feature with linear classifier and improve the classification accuracy, a deep learning network named kernel principal component analysis network…
Joint Deep Cross-Domain Transfer Learning for Emotion Recognition
Dung Nguyen, Sridha Sridharan, Duc Thanh Nguyen +4
Deep learning has been applied to achieve significant progress in emotion recognition. Despite such substantial progress, existing approaches are still hindered by insufficient tra…
Error Gradient-based Variable-Lp Norm Constraint LMS Algorithm for Sparse System Identification
Yong Feng, Fei Chen, Rui Zeng +2
Sparse adaptive filtering has gained much attention due to its wide applicability in the field of signal processing. Among the main algorithm families, sparse norm constraint adapt…
Better Lightweight Network for Free: Codeword Mimic Learning for Massive MIMO CSI feedback
Zhilin Lu, Xudong Zhang, Rui Zeng +1
The channel state information (CSI) needs to be fed back from the user equipment (UE) to the base station (BS) in frequency division duplexing (FDD) multiple-input multiple-output…
Contextual and Seasonal LSTMs for Time Series Anomaly Detection
Lingpei Zhang, Qingming Li, Yong Yang +4
Univariate time series (UTS), where each timestamp records a single variable, serve as crucial indicators in web systems and cloud servers. Anomaly detection in UTS plays an essent…
GCNs-Net: A Graph Convolutional Neural Network Approach for Decoding Time-resolved EEG Motor Imagery Signals
Yimin Hou, Shuyue Jia, Xiangmin Lun +5
Towards developing effective and efficient brain-computer interface (BCI) systems, precise decoding of brain activity measured by electroencephalogram (EEG), is highly demanded. Tr…
Navigating the Risks: A Survey of Security, Privacy, and Ethics Threats in LLM-Based Agents
Yuyou Gan, Yong Yang, Zhe Ma +10
With the continuous development of large language models (LLMs), transformer-based models have made groundbreaking advances in numerous natural language processing (NLP) tasks, lea…
Deep Auto-Encoders with Sequential Learning for Multimodal Dimensional Emotion Recognition
Dung Nguyen, Duc Thanh Nguyen, Rui Zeng +5
Multimodal dimensional emotion recognition has drawn a great attention from the affective computing community and numerous schemes have been extensively investigated, making a sign…
Gradient Compared Lp-LMS Algorithms for Sparse System Identification
Yong Feng, Jiasong Wu, Rui Zeng +2
In this paper, we propose two novel p-norm penalty least mean square (Lp-LMS) algorithms as supplements of the conventional Lp-LMS algorithm established for sparse adaptive filteri…
Enhancing Adversarial Transferability with Adversarial Weight Tuning
Jiahao Chen, Zhou Feng, Rui Zeng +6
Deep neural networks (DNNs) are vulnerable to adversarial examples (AEs) that mislead the model while appearing benign to human observers. A critical concern is the transferability…
CLIBE: Detecting Dynamic Backdoors in Transformer-based NLP Models
Rui Zeng, Xi Chen, Yuwen Pu +3
Backdoors can be injected into NLP models to induce misbehavior when the input text contains a specific feature, known as a trigger, which the attacker secretly selects. Unlike fix…
Adversarial Pulmonary Pathology Translation for Pairwise Chest X-ray Data Augmentation
Yunyan Xing, Zongyuan Ge, Rui Zeng +4
Recent works show that Generative Adversarial Networks (GANs) can be successfully applied to chest X-ray data augmentation for lung disease recognition. However, the implausible an…
MTRNet++: One-stage Mask-based Scene Text Eraser
Osman Tursun, Simon Denman, Rui Zeng +3
A precise, controllable, interpretable and easily trainable text removal approach is necessary for both user-specific and large-scale text removal applications. To achieve this, we…
Tensor object classification via multilinear discriminant analysis network
Rui Zeng, Jiasong Wu, Lotfi Senhadji +1
This paper proposes a multilinear discriminant analysis network (MLDANet) for the recognition of multidimensional objects, known as tensor objects. The MLDANet is a variation of li…
Geometry-constrained Car Recognition Using a 3D Perspective Network
Rui Zeng, Zongyuan Ge, Simon Denman +2
We present a novel learning framework for vehicle recognition from a single RGB image. Unlike existing methods which only use attention mechanisms to locate 2D discriminative infor…
Understanding and Mitigating Prompt Leaking Attacks in Real-World LLM-Based Applications
Yong Yang, Chong Fu, Tong Zhang +6
Large language model (LLM)-based applications rely on system prompts to encode core logic and developer-defined constraints, making these prompts important intellectual property. H…
Enhancing Automatic Modulation Recognition through Robust Global Feature Extraction
Yunpeng Qu, Zhilin Lu, Rui Zeng +2
Automatic Modulation Recognition (AMR) plays a crucial role in wireless communication systems. Deep learning AMR strategies have achieved tremendous success in recent years. Modula…
Quantization Adaptor for Bit-Level Deep Learning-Based Massive MIMO CSI Feedback
Xudong Zhang, Zhilin Lu, Rui Zeng +1
In massive multiple-input multiple-output (MIMO) systems, the user equipment (UE) needs to feed the channel state information (CSI) back to the base station (BS) for the following…
Multilinear Principal Component Analysis Network for Tensor Object Classification
Rui Zeng, Jiasong Wu, Zhuhong Shao +2
The recently proposed principal component analysis network (PCANet) has been proved high performance for visual content classification. In this letter, we develop a tensorial exten…
Non-volatile Reconfigurable Digital Optical Diffractive Neural Network Based on Phase Change Material
Chu Wu, Jingyu Zhao, Qiaomu Hu +2
Optical diffractive neural networks have triggered extensive research with their low power consumption and high speed in image processing. In this work, we propose a reconfigurable…
MTRNet: A Generic Scene Text Eraser
Osman Tursun, Rui Zeng, Simon Denman +3
Text removal algorithms have been proposed for uni-lingual scripts with regular shapes and layouts. However, to the best of our knowledge, a generic text removal method which is ab…
AEIOU: A Unified Defense Framework against NSFW Prompts in Text-to-Image Models
Yiming Wang, Jiahao Chen, Qingming Li +4
As text-to-image (T2I) models advance and gain widespread adoption, their associated safety concerns are becoming increasingly critical. Malicious users exploit these models to gen…
Towards Efficient Subarray Hybrid Beamforming: Attention Network-based Practical Feedback in FDD Massive MU-MIMO Systems
Zhilin Lu, Xudong Zhang, Rui Zeng +1
Channel state information (CSI) feedback is necessary for the frequency division duplexing (FDD) multiple input multiple output (MIMO) systems due to the channel non-reciprocity. W…