194 citations · 679 across the 30 of their papers we have counts for
30 papers
NP-SemiSeg: When Neural Processes meet Semi-Supervised Semantic Segmentation
Jianfeng Wang, Daniela Massiceti, Xiaolin Hu +2
Semi-supervised semantic segmentation involves assigning pixel-wise labels to unlabeled images at training time. This is useful in a wide range of real-world applications where col…
NP-Match: Towards a New Probabilistic Model for Semi-Supervised Learning
Jianfeng Wang, Xiaolin Hu, Thomas Lukasiewicz
Semi-supervised learning (SSL) has been widely explored in recent years, and it is an effective way of leveraging unlabeled data to reduce the reliance on labeled data. In this wor…
NP-Match: When Neural Processes meet Semi-Supervised Learning
Jianfeng Wang, Thomas Lukasiewicz, Daniela Massiceti +3
Semi-supervised learning (SSL) has been widely explored in recent years, and it is an effective way of leveraging unlabeled data to reduce the reliance on labeled data. In this wor…
Rethinking Bayesian Deep Learning Methods for Semi-Supervised Volumetric Medical Image Segmentation
Jianfeng Wang, Thomas Lukasiewicz
Recently, several Bayesian deep learning methods have been proposed for semi-supervised medical image segmentation. Although they have achieved promising results on medical benchma…
RSG: A Simple but Effective Module for Learning Imbalanced Datasets
Jianfeng Wang, Thomas Lukasiewicz, Xiaolin Hu +2
Imbalanced datasets widely exist in practice and area great challenge for training deep neural models with agood generalization on infrequent classes. In this work, wepropose a new…
Convolutional Neural Networks with Gated Recurrent Connections
Jianfeng Wang, Xiaolin Hu
The convolutional neural network (CNN) has become a basic model for solving many computer vision problems. In recent years, a new class of CNNs, recurrent convolution neural networ…