1 citations · 2 across the 11 of their papers we have counts for
12 papers
EKPC: Elastic Knowledge Preservation and Compensation for Class-Incremental Learning
Huaijie Wang, De Cheng, Lingfeng He +4
Class-Incremental Learning (CIL) aims to enable AI models to continuously learn from sequentially arriving data of different classes over time while retaining previously acquired k…
FCA2: Frame Compression-Aware Autoencoder for Modular and Fast Compressed Video Super-Resolution
Zhaoyang Wang, Jie Li, Wen Lu +3
State-of-the-art (SOTA) compressed video super-resolution (CVSR) models face persistent challenges, including prolonged inference time, complex training pipelines, and reliance on…
One-Step Diffusion-based Real-World Image Super-Resolution with Visual Perception Distillation
Xue Wu, Jingwei Xin, Zhijun Tu +4
Diffusion-based models have been widely used in various visual generation tasks, showing promising results in image super-resolution (SR), while typically being limited by dozens o…
Infrared and Visible Image Fusion with Hierarchical Human Perception
Guang Yang, Jie Li, Xin Liu +2
Image fusion combines images from multiple domains into one image, containing complementary information from source domains. Existing methods take pixel intensity, texture and high…
Pulmonary Embolism Mortality Prediction Using Multimodal Learning Based on Computed Tomography Angiography and Clinical Data
Zhusi Zhong, Helen Zhang, Fayez H. Fayad +12
Purpose: Pulmonary embolism (PE) is a significant cause of mortality in the United States. The objective of this study is to implement deep learning (DL) models using Computed Tomo…
An Information Compensation Framework for Zero-Shot Skeleton-based Action Recognition
Haojun Xu, Yan Gao, Jie Li +1
Zero-shot human skeleton-based action recognition aims to construct a model that can recognize actions outside the categories seen during training. Previous research has focused on…
MindSemantix: Deciphering Brain Visual Experiences with a Brain-Language Model
Ziqi Ren, Jie Li, Xuetong Xue +4
Deciphering the human visual experience through brain activities captured by fMRI represents a compelling and cutting-edge challenge in the field of neuroscience research. Compared…
Multi-modality Regional Alignment Network for Covid X-Ray Survival Prediction and Report Generation
Zhusi Zhong, Jie Li, John Sollee +7
In response to the worldwide COVID-19 pandemic, advanced automated technologies have emerged as valuable tools to aid healthcare professionals in managing an increased workload by…
Region-specific Risk Quantification for Interpretable Prognosis of COVID-19
Zhusi Zhong, Jie Li, Zhuoqi Ma +7
The COVID-19 pandemic has strained global public health, necessitating accurate diagnosis and intervention to control disease spread and reduce mortality rates. This paper introduc…
Diffusion Model Based Visual Compensation Guidance and Visual Difference Analysis for No-Reference Image Quality Assessment
Zhaoyang Wang, Bo Hu, Mingyang Zhang +4
Existing free-energy guided No-Reference Image Quality Assessment (NR-IQA) methods still suffer from finding a balance between learning feature information at the pixel level of th…
A Dual Domain Multi-exposure Image Fusion Network based on the Spatial-Frequency Integration
Guang Yang, Jie Li, Xinbo Gao
Multi-exposure image fusion aims to generate a single high-dynamic image by integrating images with different exposures. Existing deep learning-based multi-exposure image fusion me…
A Multi-scale Information Integration Framework for Infrared and Visible Image Fusion
Guang Yang, Jie Li, Hanxiao Lei +1
Infrared and visible image fusion aims at generating a fused image containing the intensity and detail information of source images, and the key issue is effectively measuring and…