32 citations · 55 across the 7 of their papers we have counts for
7 papers
Few-Shot Learning with Visual Distribution Calibration and Cross-Modal Distribution Alignment
Runqi Wang, Hao Zheng, Xiaoyue Duan +5
Pre-trained vision-language models have inspired much research on few-shot learning. However, with only a few training images, there exist two crucial problems: (1) the visual feat…
SurfNN: Joint Reconstruction of Multiple Cortical Surfaces from Magnetic Resonance Images
Hao Zheng, Hongming Li, Yong Fan
To achieve fast, robust, and accurate reconstruction of the human cortical surfaces from 3D magnetic resonance images (MRIs), we develop a novel deep learning-based framework, refe…
SPDA: Superpixel-based Data Augmentation for Biomedical Image Segmentation
Yizhe Zhang, Lin Yang, Hao Zheng +5
Supervised training a deep neural network aims to "teach" the network to mimic human visual perception that is represented by image-and-label pairs in the training data. Superpixel…
Cascade Decoder: A Universal Decoding Method for Biomedical Image Segmentation
Peixian Liang, Jianxu Chen, Hao Zheng +3
The Encoder-Decoder architecture is a main stream deep learning model for biomedical image segmentation. The encoder fully compresses the input and generates encoded features, and…
A New Ensemble Learning Framework for 3D Biomedical Image Segmentation
Hao Zheng, Yizhe Zhang, Lin Yang +4
3D image segmentation plays an important role in biomedical image analysis. Many 2D and 3D deep learning models have achieved state-of-the-art segmentation performance on 3D biomed…
Deep Learning Based Instance Segmentation in 3D Biomedical Images Using Weak Annotation
Zhuo Zhao, Lin Yang, Hao Zheng +3
Instance segmentation in 3D images is a fundamental task in biomedical image analysis. While deep learning models often work well for 2D instance segmentation, 3D instance segmenta…
BoxNet: Deep Learning Based Biomedical Image Segmentation Using Boxes Only Annotation
Lin Yang, Yizhe Zhang, Zhuo Zhao +5
In recent years, deep learning (DL) methods have become powerful tools for biomedical image segmentation. However, high annotation efforts and costs are commonly needed to acquire…