no code implementations • 3 Jun 2023 • Tao Lei, Yetong Xu, Hailong Ning, Zhiyong Lv, Chongdan Min, Yaochu Jin, Asoke K. Nandi
Popular Transformer networks have been successfully applied to remote sensing (RS) image change detection (CD) identifications and achieve better results than most convolutional neural networks (CNNs), but they still suffer from two main problems.
1 code implementation • IEEE Transactions on Geoscience and Remote Sensing 2023 • Tao Lei, Xinzhe Geng, Hailong Ning, Zhiyong Lv, Maoguo Gong, Yaochu Jin, Asoke K. Nandi
First, the existing multiscale feature fusion methods often use redundant feature extraction and fusion strategies, which often lead to high computational costs and memory usage.
Ranked #2 on Change Detection on DSIFN-CD
Building change detection for remote sensing images Change Detection +1
no code implementations • 20 Nov 2021 • YiPeng Zhang, Bingliang Hu, Hailong Ning, Quang Wang
The AdaReLU can dynamically adjust the slope parameters according to the target style and can be utilized to increase the controllability by combining with Adaptive Instance Normalization (AdaIN).
no code implementations • 17 Sep 2021 • Hailong Ning, Bin Zhao, Zhanxuan Hu, Lang He, Ercheng Pei
Motivated by this, an audio-visual collaborative representation learning method is proposed for the DSP task, which explores the audio modality to better predict the dynamic saliency map by assisting vision modality.
no code implementations • 9 Mar 2021 • Yuan Yuan, Hailong Ning, Xiaoqiang Lu
In this paper, a novel VAP method is proposed to generate visual attention map via bio-inspired representation learning.