1 citations · 3 across the 6 of their papers we have counts for
7 papers
Knowledge Condensation Distillation
Chenxin Li, Mingbao Lin, Zhiyuan Ding +5
Knowledge Distillation (KD) transfers the knowledge from a high-capacity teacher network to strengthen a smaller student. Existing methods focus on excavating the knowledge hints a…
A Closer Look at Personalization in Federated Image Classification
Changxing Jing, Yan Huang, Yihong Zhuang +4
Federated Learning (FL) is developed to learn a single global model across the decentralized data, while is susceptible when realizing client-specific personalization in the presen…
Harmonizing Pathological and Normal Pixels for Pseudo-healthy Synthesis
Yunlong Zhang, Xin Lin, Yihong Zhuang +6
Synthesizing a subject-specific pathology-free image from a pathological image is valuable for algorithm development and clinical practice. In recent years, several approaches base…
Self-Verification in Image Denoising
Huangxing Lin, Yihong Zhuang, Delu Zeng +3
We devise a new regularization, called self-verification, for image denoising. This regularization is formulated using a deep image prior learned by the network, rather than a trad…
Adaptive noise imitation for image denoising
Huangxing Lin, Yihong Zhuang, Yue Huang +4
The effectiveness of existing denoising algorithms typically relies on accurate pre-defined noise statistics or plenty of paired data, which limits their practicality. In this work…
Generator Versus Segmentor: Pseudo-healthy Synthesis
Zhang Yunlong, Li Chenxin, Lin Xin +6
This paper investigates the problem of pseudo-healthy synthesis that is defined as synthesizing a subject-specific pathology-free image from a pathological one. Recent approaches b…