Search Results for author:
Found 7 papers, 5 papers with code
MH-pFLGB: Model Heterogeneous personalized Federated Learning via Global Bypass for Medical Image Analysis
In the evolving application of medical artificial intelligence, federated learning is notable for its ability to protect training data privacy.
pFLFE: Cross-silo Personalized Federated Learning via Feature Enhancement on Medical Image Segmentation
In medical image segmentation, personalized cross-silo federated learning (FL) is becoming popular for utilizing varied data across healthcare settings to overcome data scarcity and privacy concerns.
I$^2$VC: A Unified Framework for Intra- & Inter-frame Video Compression
Previous neural video compression methods necessitate distinct codecs for three types of frames (I-frame, P-frame and B-frame), which hinders a unified approach and generalization across different video contexts.
IBVC: Interpolation-driven B-frame Video Compression
Learned B-frame video compression aims to adopt bi-directional motion estimation and motion compensation (MEMC) coding for middle frame reconstruction.
A simple normalization technique using window statistics to improve the out-of-distribution generalization on medical images
In this study, we present a novel normalization technique called window normalization (WIN) to improve the model generalization on heterogeneous medical images, which is a simple yet effective alternative to existing normalization methods.
JNMR: Joint Non-linear Motion Regression for Video Frame Interpolation
Video frame interpolation (VFI) aims to generate predictive frames by warping learnable motions from the bidirectional historical references.
An attention-based Bi-GRU-CapsNet model for hypernymy detection between compound entities
In this paper, we present an attention-based Bi-GRU-CapsNet model to detect hypernymy relationship between compound entities.
