Explicit Change Relation Learning for Change Detection in VHR Remote Sensing Images

no code implementations • 14 Nov 2023 • Dalong Zheng, Zebin Wu, Jia Liu, Chih-Cheng Hung, Zhihui Wei

In order to fully mine these three kinds of change features, we propose the triple branch network combining the transformer and convolutional neural network (CNN) to extract and fuse these change features from two perspectives of global information and local information, respectively.

Binary Classification Change Detection +1

An Unpaired Cross-modality Segmentation Framework Using Data Augmentation and Hybrid Convolutional Networks for Segmenting Vestibular Schwannoma and Cochlea

no code implementations • 28 Nov 2022 • Yuzhou Zhuang, Hong Liu, Enmin Song, Coskun Cetinkaya, Chih-Cheng Hung

We adopt two data augmentation methods for effectively learning the semantic information and generating realistic target domain scans: generative and online data augmentation.

Data Augmentation Segmentation

Dual-branch residual network for lung nodule segmentation

no code implementations • 21 May 2019 • Haichao Cao, Hong Liu, Enmin Song, Chih-Cheng Hung, Guangzhi Ma, Xiangyang Xu, Renchao Jin, Jianguo Lu

Experimental results show that the DB-ResNet achieves superior segmentation performance with an average dice score of 82. 74% on the dataset.

Computed Tomography (CT) Lung Nodule Segmentation +1

Two-Stage Convolutional Neural Network Architecture for Lung Nodule Detection

no code implementations • 9 May 2019 • Haichao Cao, Hong Liu, Enmin Song, Guangzhi Ma, Xiangyang Xu, Renchao Jin, Tengying Liu, Chih-Cheng Hung

The CNN architecture in the first stage is based on the improved UNet segmentation network to establish an initial detection of lung nodules.

Computed Tomography (CT) Data Augmentation +4