45 citations · 60 across the 3 of their papers we have counts for
3 papers
eess.IV2023★ 4 cited
Narrowing the semantic gaps in U-Net with learnable skip connections: The case of medical image segmentation
Haonan Wang, Peng Cao, Xiaoli Liu +2
Most state-of-the-art methods for medical image segmentation adopt the encoder-decoder architecture. However, this U-shaped framework still has limitations in capturing the non-loc…
cs.LG2022★ 11 cited
Rank-N-Contrast: Learning Continuous Representations for Regression
Kaiwen Zha, Peng Cao, Jeany Son +2
Deep regression models typically learn in an end-to-end fashion without explicitly emphasizing a regression-aware representation. Consequently, the learned representations exhibit…
cs.CV2021★ 45 cited
UCTransNet: Rethinking the Skip Connections in U-Net from a Channel-wise Perspective with Transformer
Haonan Wang, Peng Cao, Jiaqi Wang +1
Most recent semantic segmentation methods adopt a U-Net framework with an encoder-decoder architecture. It is still challenging for U-Net with a simple skip connection scheme to mo…