13 citations · 37 across the 13 of their papers we have counts for
14 papers
OGG-FR: Orthogonal Gradient Gaming and Frequency Rectification for Unmanned Aerial Vehicle Infrared Image Super-Resolution
Yongsong Huang, Qingzhong Wang, Xiaofeng Liu +3
Unmanned aerial vehicle (UAV) infrared image super-resolution aims to recover weak thermal structures for deployment on resource-constrained platforms; lightweight models are there…
Right Answer, Wrong Heat: Explanation-Aware Evaluation and Thermal-Grounded Feedback for MLLMs on Infrared Images
Yongsong Huang, Xiaofeng Liu, Tomo Miyazaki +2
General-purpose multimodal large language models (MLLMs) are increasingly applied to infrared images, where they are commonly scored by answer accuracy alone. However, a correct an…
Improving Adversarial Robustness via Activation Amplification and Attenuation
Taïga Gonçalves, Yongsong Huang, Tomo Miyazaki +1
The existence of adversarial attacks is often attributed to the presence of non-robust features in neural networks. While prior defenses reduce their impact via pruning, masking, o…
POCA: Pareto-Optimal Curriculum Alignment for Visual Text Generation
Yaohou Fan, Qingzhong Wang, Yongsong Huang +3
Current visual text generation models struggle with the trade-off between text accuracy and overall image coherence. We find that achieving high text accuracy can reduce aesthetic…
GTFMN: Guided Texture and Feature Modulation Network for Low-Light Image Enhancement and Super-Resolution
Yongsong Huang, Tzu-Hsuan Peng, Tomo Miyazaki +4
Low-light image super-resolution (LLSR) is a challenging task due to the coupled degradation of low resolution and poor illumination. To address this, we propose the Guided Texture…
GPSMamba: A Global Phase and Spectral Prompt-guided Mamba for Infrared Image Super-Resolution
Yongsong Huang, Tomo Miyazaki, Xiaofeng Liu +1
Infrared Image Super-Resolution (IRSR) is challenged by the low contrast and sparse textures of infrared data, requiring robust long-range modeling to maintain global coherence. Wh…
IRSRMamba: Infrared Image Super-Resolution via Mamba-based Wavelet Transform Feature Modulation Model
Yongsong Huang, Tomo Miyazaki, Xiaofeng Liu +1
Infrared image super-resolution demands long-range dependency modeling and multi-scale feature extraction to address challenges such as homogeneous backgrounds, weak edges, and spa…
Learn From Orientation Prior for Radiograph Super-Resolution: Orientation Operator Transformer
Yongsong Huang, Tomo Miyazaki, Xiaofeng Liu +3
Background and objective: High-resolution radiographic images play a pivotal role in the early diagnosis and treatment of skeletal muscle-related diseases. It is promising to enhan…
Infrared Image Super-Resolution via GAN
Yongsong Huang, Shinichiro Omachi
The ability of generative models to accurately fit data distributions has resulted in their widespread adoption and success in fields such as computer vision and natural language p…
Texture and Noise Dual Adaptation for Infrared Image Super-Resolution
Yongsong Huang, Tomo Miyazaki, Xiaofeng Liu +2
Recent efforts have explored leveraging visible light images to enrich texture details in infrared (IR) super-resolution. However, this direct adaptation approach often becomes a d…
Vicinal Feature Statistics Augmentation for Federated 3D Medical Volume Segmentation
Yongsong Huang, Wanqing Xie, Mingzhen Li +5
Federated learning (FL) enables multiple client medical institutes collaboratively train a deep learning (DL) model with privacy protection. However, the performance of FL can be c…
Infrared Image Super-Resolution: Systematic Review, and Future Trends
Yongsong Huang, Tomo Miyazaki, Xiaofeng Liu +1
Image Super-Resolution (SR) is essential for a wide range of computer vision and image processing tasks. Investigating infrared (IR) image (or thermal images) super-resolution is a…
Rethinking Degradation: Radiograph Super-Resolution via AID-SRGAN
Yongsong Huang, Qingzhong Wang, Shinichiro Omachi
In this paper, we present a medical AttentIon Denoising Super Resolution Generative Adversarial Network (AID-SRGAN) for diographic image super-resolution. First, we present a medic…
Infrared Image Super-Resolution via Heterogeneous Convolutional WGAN
Yongsong Huang, Zetao Jiang, Qingzhong Wang +2
Image super-resolution is important in many fields, such as surveillance and remote sensing. However, infrared (IR) images normally have low resolution since the optical equipment…