3 papers
eess.IV2026
A Data-driven Loss Weighting Scheme across Heterogeneous Tasks for Image Denoising
Xiangyu Rui, Xiangyong Cao, Xile Zhao +2
In a variational denoising model, weight in the data fidelity term plays the role of enhancing the noise-removal capability. It is profoundly correlated with noise information, whi…
cs.CV2025
HIDFlowNet: A Flow-Based Deep Network for Hyperspectral Image Denoising
Qizhou Wang, Li Pang, Xiangyong Cao +2
Hyperspectral image (HSI) denoising is essentially ill-posed since a noisy HSI can be degraded from multiple clean HSIs. However, existing deep learning (DL)-based approaches only…
cs.LG2025
Discovering Influential Factors in Variational Autoencoders
Shiqi Liu, Jingxin Liu, Qian Zhao +5
In the field of machine learning, it is still a critical issue to identify and supervise the learned representation without manually intervening or intuition assistance to extract…