1 code implementation • 1 Aug 2021 • Haitong Tang, Shuang He, Mengduo Yang, Xia Lu, Qin Yu, Kaiyue Liu, Hongjie Yan, Nizhuan Wang
Through extensive analysis and experiments, we provided credible evidence showing that the multi-layer convolutional sparse coding block enables semantic segmentation model to converge faster, can extract finer semantic and appearance information of images, and improve the ability to recover spatial detail information.
no code implementations • 19 Sep 2021 • Shuang He, Xia Lu, Jason Gu, Haitong Tang, Qin Yu, Kaiyue Liu, Haozhou Ding, Chunqi Chang, Nizhuan Wang
For semantic segmentation of remote sensing images (RSI), trade-off between representation power and location accuracy is quite important.
no code implementations • 7 Oct 2021 • Shuang He, Haitong Tang, Xia Lu, Hongjie Yan, Nizhuan Wang
Specifically, our MSHCNet adopted four parallel streams, which contained G-stream, utilizing the irregular correlation between adjacent land covers in terms of first-order graph in non-Euclidean space; C-stream, adopting convolution operator to learn regular spatial-spectral features in Euclidean space; N-stream, combining first and second order features to learn representative and discriminative regular spatial-spectral features of Euclidean space; S-stream, using GSOP to capture boundary correlations and obtain graph representations from all nodes in graphs of non-Euclidean space.
1 code implementation • 28 Mar 2022 • Haitong Tang, Shuang He, Lingbin Bian, Zhiming Cui, Nizhuan Wang
Specifically, we first propose a novel width-depth synchronous extension-based basis pursuit (WSEBP) algorithm which solves the ML-CSC problem without the limitation of the number of iterations compared to the SOTA algorithms and maximizes the performance by an effective initialization in each layer.
no code implementations • 7 Jul 2022 • Xiangxi Meng, Yuning Gu, Yongsheng Pan, Nizhuan Wang, Peng Xue, Mengkang Lu, Xuming He, Yiqiang Zhan, Dinggang Shen
Multi-modal medical image completion has been extensively applied to alleviate the missing modality issue in a wealth of multi-modal diagnostic tasks.
no code implementations • 18 Jan 2023 • Lingbin Bian, Nizhuan Wang, Leonardo Novelli, Jonathan Keith, Adeel Razi
The method can robustly detect the group-level community structure of weighted functional networks that give rise to hidden brain states with an unknown number of communities and retain the variability of individual networks.
1 code implementation • 14 Feb 2023 • Kaiyue Liu, Qi Sun, Daming Sun, Mengduo Yang, Nizhuan Wang
Underwater target detection is a crucial aspect of ocean exploration.
1 code implementation • 24 Jul 2023 • Han Wu, Jiadong Zhang, Yu Fang, Zhentao Liu, Nizhuan Wang, Zhiming Cui, Dinggang Shen
Additionally, we further propose a Sequence Loss to maintain the sequential structure embedded along the vertebrae.