most citedSemi-supervision semantic segmentation with uncertainty-guided self cross supervision

4 citations · 8 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV20231 cited

HyperDID: Hyperspectral Intrinsic Image Decomposition with Deep Feature Embedding

Zhiqiang Gong, Xian Zhou, Wen Yao +2

The dissection of hyperspectral images into intrinsic components through hyperspectral intrinsic image decomposition (HIID) enhances the interpretability of hyperspectral data, pro…

cs.LG2022

Algorithms for Bayesian network modeling and reliability inference of complex multistate systems: Part II-Dependent systems

Xiaohu Zheng, Wen Yao, Xiaoqian Chen

In using the Bayesian network (BN) to construct the complex multistate system's reliability model as described in Part I, the memory storage requirements of the node probability ta…

cs.LG2022

Consistency regularization-based Deep Polynomial Chaos Neural Network Method for Reliability Analysis

Xiaohu Zheng, Wen Yao, Yunyang Zhang +1

Polynomial chaos expansion (PCE) is a powerful surrogate model-based reliability analysis method. Generally, a PCE model with a higher expansion order is usually required to obtain…

cs.CV20224 cited

Semi-supervision semantic segmentation with uncertainty-guided self cross supervision

Yunyang Zhang, Zhiqiang Gong, Xiaohu Zheng +2

As a powerful way of realizing semi-supervised segmentation, the cross supervision method learns cross consistency based on independent ensemble models using abundant unlabeled ima…

cs.CV2022

Contrastive Enhancement Using Latent Prototype for Few-Shot Segmentation

Xiaoyu Zhao, Xiaoqian Chen, Zhiqiang Gong +3

Few-shot segmentation enables the model to recognize unseen classes with few annotated examples. Most existing methods adopt prototype learning architecture, where support prototyp…

cs.LG20222 cited

Physics-Informed Deep Monte Carlo Quantile Regression method for Interval Multilevel Bayesian Network-based Satellite Heat Reliability Analysis

Xiaohu Zheng, Wen Yao, Zhiqiang Gong +2

Temperature field reconstruction is essential for analyzing satellite heat reliability. As a representative machine learning model, the deep convolutional neural network (DCNN) is…