34 citations · 69 across the 28 of their papers we have counts for
28 papers
Evidence-Based Actor-Verifier Reasoning for Echocardiographic Agents
Peng Huang, Yiming Wang, Yineng Chen +9
Echocardiography plays an important role in the screening and diagnosis of cardiovascular diseases. However, automated intelligent analysis of echocardiographic data remains challe…
DAGLFNet: Deep Feature Attention Guided Global and Local Feature Fusion for Pseudo-Image Point Cloud Segmentation
Chuang Chen, Yi Lin, Bo Wang +3
Environmental perception systems are crucial for high-precision mapping and autonomous navigation, with LiDAR serving as a core sensor providing accurate 3D point cloud data. Effic…
RLMiniStyler: Light-weight RL Style Agent for Arbitrary Sequential Neural Style Generation
Jing Hu, Chengming Feng, Shu Hu +4
Arbitrary style transfer aims to apply the style of any given artistic image to another content image. Still, existing deep learning-based methods often require significant computa…
Real-Time Animatable 2DGS-Avatars with Detail Enhancement from Monocular Videos
Xia Yuan, Hai Yuan, Wenyi Ge +3
High-quality, animatable 3D human avatar reconstruction from monocular videos offers significant potential for reducing reliance on complex hardware, making it highly practical for…
Diffusion-empowered AutoPrompt MedSAM
Peng Huang, Shu Hu, Bo Peng +5
MedSAM, a medical foundation model derived from the SAM architecture, has demonstrated notable success across diverse medical domains. However, its clinical application faces two m…
LLM-MedQA: Enhancing Medical Question Answering through Case Studies in Large Language Models
Hang Yang, Hao Chen, Hui Guo +6
Accurate and efficient question-answering systems are essential for delivering high-quality patient care in the medical field. While Large Language Models (LLMs) have made remarkab…
Teacher Encoder-Student Decoder Denoising Guided Segmentation Network for Anomaly Detection
Shixuan Song, Hao Chen, Shu Hu +3
Visual anomaly detection is a highly challenging task, often categorized as a one-class classification and segmentation problem. Recent studies have demonstrated that the student-t…
A Self-Learning Multimodal Approach for Fake News Detection
Hao Chen, Hui Guo, Baochen Hu +5
The rapid growth of social media has resulted in an explosion of online news content, leading to a significant increase in the spread of misleading or false information. While mach…
An Explainable Non-local Network for COVID-19 Diagnosis
Jingfu Yang, Peng Huang, Jing Hu +5
The CNN has achieved excellent results in the automatic classification of medical images. In this study, we propose a novel deep residual 3D attention non-local network (NL-RAN) to…
Robustly Optimized Deep Feature Decoupling Network for Fatty Liver Diseases Detection
Peng Huang, Shu Hu, Bo Peng +3
Current medical image classification efforts mainly aim for higher average performance, often neglecting the balance between different classes. This can lead to significant differe…
MetaSD: A Unified Framework for Scalable Downscaling of Meteorological Variables in Diverse Situations
Jing Hu, Honghu Zhang, Peng Zheng +3
Addressing complex meteorological processes at a fine spatial resolution requires substantial computational resources. To accelerate meteorological simulations, researchers have ut…
Masked Conditional Diffusion Model for Enhancing Deepfake Detection
Tiewen Chen, Shanmin Yang, Shu Hu +4
Recent studies on deepfake detection have achieved promising results when training and testing faces are from the same dataset. However, their results severely degrade when confron…
Uncertainty-Aware Explainable Recommendation with Large Language Models
Yicui Peng, Hao Chen, Chingsheng Lin +7
Providing explanations within the recommendation system would boost user satisfaction and foster trust, especially by elaborating on the reasons for selecting recommended items tai…
Efficient Image Super-Resolution via Symmetric Visual Attention Network
Chengxu Wu, Qinrui Fan, Shu Hu +3
An important development direction in the Single-Image Super-Resolution (SISR) algorithms is to improve the efficiency of the algorithms. Recently, efficient Super-Resolution (SR)…
X-Transfer: A Transfer Learning-Based Framework for GAN-Generated Fake Image Detection
Lei Zhang, Hao Chen, Shu Hu +5
Generative adversarial networks (GANs) have remarkably advanced in diverse domains, especially image generation and editing. However, the misuse of GANs for generating deceptive im…
CrossDF: Improving Cross-Domain Deepfake Detection with Deep Information Decomposition
Shanmin Yang, Hui Guo, Shu Hu +5
Deepfake technology poses a significant threat to security and social trust. Although existing detection methods have shown high performance in identifying forgeries within dataset…
Controlling Neural Style Transfer with Deep Reinforcement Learning
Chengming Feng, Jing Hu, Xin Wang +5
Controlling the degree of stylization in the Neural Style Transfer (NST) is a little tricky since it usually needs hand-engineering on hyper-parameters. In this paper, we propose t…
RL-I2IT: Image-to-Image Translation with Deep Reinforcement Learning
Jing Hu, Ziwei Luo, Chengming Feng +7
Most existing Image-to-Image Translation (I2IT) methods generate images in a single run of a deep learning (DL) model. However, designing such a single-step model is always challen…
Harnessing the Power of Text-image Contrastive Models for Automatic Detection of Online Misinformation
Hao Chen, Peng Zheng, Xin Wang +5
As growing usage of social media websites in the recent decades, the amount of news articles spreading online rapidly, resulting in an unprecedented scale of potentially fraudulent…
Attacking Important Pixels for Anchor-free Detectors
Yunxu Xie, Shu Hu, Xin Wang +4
Deep neural networks have been demonstrated to be vulnerable to adversarial attacks: subtle perturbation can completely change the prediction result. Existing adversarial attacks o…
RMBench: Benchmarking Deep Reinforcement Learning for Robotic Manipulator Control
Yanfei Xiang, Xin Wang, Shu Hu +4
Reinforcement learning is applied to solve actual complex tasks from high-dimensional, sensory inputs. The last decade has developed a long list of reinforcement learning algorithm…
Stochastic Actor-Executor-Critic for Image-to-Image Translation
Ziwei Luo, Jing Hu, Xin Wang +5
Training a model-free deep reinforcement learning model to solve image-to-image translation is difficult since it involves high-dimensional continuous state and action spaces. In t…
Stochastic Planner-Actor-Critic for Unsupervised Deformable Image Registration
Ziwei Luo, Jing Hu, Xin Wang +6
Large deformations of organs, caused by diverse shapes and nonlinear shape changes, pose a significant challenge for medical image registration. Traditional registration methods ne…
Adaptive Warden Strategy for Countering Network Covert Storage Channels
Mehdi Chourib, Steffen Wendzel, Wojciech Mazurczyk
The detection and elimination of covert channels are performed by a network node, known as a warden. Especially if faced with adaptive covert communication parties, a regular warde…