Search Results for author:
Found 7 papers, 1 papers with code
DDPET-3D: Dose-aware Diffusion Model for 3D Ultra Low-dose PET Imaging
We extensively evaluated DDPET-3D on 100 patients with 6 different low-dose levels (a total of 600 testing studies), and demonstrated superior performance over previous diffusion models for 3D imaging problems as well as previous noise-aware medical image denoising models.
A Lifetime Extended Energy Management Strategy for Fuel Cell Hybrid Electric Vehicles via Self-Learning Fuzzy Reinforcement Learning
In the paper, a fuzzy reinforcement learning-based energy management strategy for fuel cell hybrid electric vehicles is proposed to reduce fuel consumption, maintain the batteries' long-term operation, and extend the lifetime of the fuel cells system.
Multi-scale temporal-frequency attention for music source separation
In recent years, deep neural networks (DNNs) based approaches have achieved the start-of-the-art performance for music source separation (MSS).
A two-step backward compatible fullband speech enhancement system
Speech enhancement methods based on deep learning have surpassed traditional methods.
A Causal U-net based Neural Beamforming Network for Real-Time Multi-Channel Speech Enhancement
In this work, a new causal U-net based multiple-in-multiple-out structure is proposed for real-time multi-channel speech enhancement.
Dissipative solutions to the compressible isentropic Navier-Stokes equations
The existence of dissipative solutions to the compressible isentropic Navier-Stokes equations was established in this paper.
Analysis of PDEs
Subsampling Bias and The Best-Discrepancy Systematic Cross Validation
Experiments with 156 benchmark datasets and three classifiers (logistic regression, decision tree and naive bayes) show that in general, our cross-validation procedure can extrude subsampling bias in the MCCV by lowering the EPE around 7. 18% and the variances around 26. 73%.
