activity
20152020
most citedFU-net: Multi-class Image Segmentation Using Feedback Weighted U-net

12 citations · 28 across the 8 of their papers we have counts for

collaborators

8 papers

cs.LG20202 cited

A Novel Meta Learning Framework for Feature Selection using Data Synthesis and Fuzzy Similarity

Zixiao Shen, Xin Chen, Jonathan M. Garibaldi

This paper presents a novel meta learning framework for feature selection (FS) based on fuzzy similarity. The proposed method aims to recommend the best FS method from four candida…

cs.LG2020

A Novel Weighted Combination Method for Feature Selection using Fuzzy Sets

Zixiao Shen, Xin Chen, Jonathan M. Garibaldi

In this paper, we propose a novel weighted combination feature selection method using bootstrap and fuzzy sets. The proposed method mainly consists of three processes, including fu…

cs.LG2020

Performance Optimization of a Fuzzy Entropy based Feature Selection and Classification Framework

Zixiao Shen, Xin Chen, Jonathan M. Garibaldi

In this paper, based on a fuzzy entropy feature selection framework, different methods have been implemented and compared to improve the key components of the framework. Those meth…

eess.IV202012 cited

FU-net: Multi-class Image Segmentation Using Feedback Weighted U-net

Mina Jafari, Ruizhe Li, Yue Xing +4

In this paper, we present a generic deep convolutional neural network (DCNN) for multi-class image segmentation. It is based on a well-established supervised end-to-end DCNN model,…

eess.IV20208 cited

DRU-net: An Efficient Deep Convolutional Neural Network for Medical Image Segmentation

Mina Jafari, Dorothee Auer, Susan Francis +2

Residual network (ResNet) and densely connected network (DenseNet) have significantly improved the training efficiency and performance of deep convolutional neural networks (DCNNs)…

cs.CV2019

Dual Adaptive Pyramid Network for Cross-Stain Histopathology Image Segmentation

Xianxu Hou, Jingxin Liu, Bolei Xu +6

Supervised semantic segmentation normally assumes the test data being in a similar data domain as the training data. However, in practice, the domain mismatch between the training…