2 citations · 2 across the 3 of their papers we have counts for
3 papers
eess.AS2023
Selective HuBERT: Self-Supervised Pre-Training for Target Speaker in Clean and Mixture Speech
Jingru Lin, Meng Ge, Wupeng Wang +2
Self-supervised pre-trained speech models were shown effective for various downstream speech processing tasks. Since they are mainly pre-trained to map input speech to pseudo-label…
eess.IV2023★ 2 cited
A review of uncertainty quantification in medical image analysis: probabilistic and non-probabilistic methods
Ling Huang, Su Ruan, Yucheng Xing +1
The comprehensive integration of machine learning healthcare models within clinical practice remains suboptimal, notwithstanding the proliferation of high-performing solutions repo…
eess.IV2022
FCSN: Global Context Aware Segmentation by Learning the Fourier Coefficients of Objects in Medical Images
Young Seok Jeon, Hongfei Yang, Mengling Feng
The encoder-decoder model is a commonly used Deep Neural Network (DNN) model for medical image segmentation. Conventional encoder-decoder models make pixel-wise predictions focusin…