1 code implementation • 9 Jun 2023 • Jie Gui, Xiaofeng Cong, Lei He, Yuan Yan Tang, James Tin-Yau Kwok
On the one hand, the dehazing task is an illposedness problem, which means that no unique solution exists.
no code implementations • 31 Mar 2023 • Biwei Cao, Lulu Hua, Jiuxin Cao, Jie Gui, Bo Liu, James Tin-Yau Kwok
Different from popular methods which take full advantage of the propagation topology structure, in this paper, we propose a novel framework for fake news detection from perspectives of semantic, emotion and data enhancement, which excavates the emotional evolution patterns of news participants during the propagation process, and a dual deep interaction channel network of semantic and emotion is designed to obtain a more comprehensive and fine-grained news representation with the consideration of comments.
1 code implementation • 30 Mar 2023 • Jie Gui, Xiaofeng Cong, Chengwei Peng, Yuan Yan Tang, James Tin-Yau Kwok
In this paper, we focus on designing a group of attack methods based on first order gradient to verify the robustness of the existing dehazing algorithms.
1 code implementation • 13 Jan 2023 • Jie Gui, Tuo Chen, Jing Zhang, Qiong Cao, Zhenan Sun, Hao Luo, DaCheng Tao
Deep supervised learning algorithms typically require a large volume of labeled data to achieve satisfactory performance.
1 code implementation • 8 Jan 2023 • Jidong Ge, Yuxiang Liu, Jie Gui, Lanting Fang, Ming Lin, James Tin-Yau Kwok, LiGuo Huang, Bin Luo
However, the relation between these two losses is not clear.
1 code implementation • 3 Dec 2022 • Wenzhe Jia, Yuan Cao, Junwei Liu, Jie Gui
When a new query arrives, only the binary codes of the corresponding potential neighbors are updated.
1 code implementation • 28 Nov 2022 • Zhengqi Liu, Jie Gui, Hao Luo
Most previous works mask patches of the image randomly, which underutilizes the semantic information that is beneficial to visual representation learning.
no code implementations • 16 Nov 2022 • Biwei Cao, Jiuxin Cao, Jie Gui, Jiayun Shen, Bo Liu, Lei He, Yuan Yan Tang, James Tin-Yau Kwok
Such approaches, however, ignore the VE's unique nature of relation inference between the premise and hypothesis.
no code implementations • 20 Oct 2021 • Jianfeng Wu, Wenhui Zhu, Yi Su, Jie Gui, Natasha Lepore, Eric M. Reiman, Richard J. Caselli, Paul M. Thompson, Kewei Chen, Yalin Wang
We evaluate our framework on 925 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI).
no code implementations • 13 Jun 2021 • Huapeng Wu, Jie Gui, Jun Zhang, James T. Kwok, Zhihui Wei
Recently, convolutional neural network (CNN) based image super-resolution (SR) methods have achieved significant performance improvement.
no code implementations • 13 Jun 2021 • Huapeng Wu, Jie Gui, Jun Zhang, James T. Kwok, Zhihui Wei
Recently, deep convolutional neural network methods have achieved an excellent performance in image superresolution (SR), but they can not be easily applied to embedded devices due to large memory cost.
1 code implementation • 7 Jun 2021 • Jie Gui, Xiaofeng Cong, Yuan Cao, Wenqi Ren, Jun Zhang, Jing Zhang, Jiuxin Cao, DaCheng Tao
With the development of convolutional neural networks, hundreds of deep learning based dehazing methods have been proposed.
no code implementations • 1 Apr 2021 • Jie Gui, Haizhang Zhang
Multi-task learning is an important trend of machine learning in facing the era of artificial intelligence and big data.
1 code implementation • 22 Mar 2021 • Yuxiang Liu, Jidong Ge, Chuanyi Li, Jie Gui
We propose Parametric Weights Standardization (PWS), a fast and robust to mini-batch size module used for conv filters, to solve the shift of the average gradient.
no code implementations • 2 Apr 2020 • Xiaoyun Li, Jie Gui, Ping Li
In this paper, we propose the kernel version of multi-view discriminant analysis, called kernel multi-view discriminant analysis (KMvDA).
no code implementations • 20 Jan 2020 • Jie Gui, Zhenan Sun, Yonggang Wen, DaCheng Tao, Jieping Ye
Generative adversarial networks (GANs) are a hot research topic recently.
no code implementations • 1 Dec 2019 • Rujing Yao, Linlin Hou, Lei Yang, Jie Gui, Qing Yin, Ou wu
This study focuses on a reverse question answering (QA) procedure, in which machines proactively raise questions and humans supply the answers.
no code implementations • 26 Sep 2019 • Huapeng Wu, Zhengxia Zou, Jie Gui, Wen-Jun Zeng, Jieping Ye, Jun Zhang, Hongyi Liu, Zhihui Wei
In this paper, we make a thorough investigation on the attention mechanisms in a SR model and shed light on how simple and effective improvements on these ideas improve the state-of-the-arts.
1 code implementation • 25 Sep 2019 • Chenxingyu Zhao, Jie Gui, Yixiao Guo, Jie Jiang, Tong Yang, Bin Cui, Gong Zhang
Unlike the densification to fill the empty bins after they undesirably occur, our design goal is to balance the load so as to reduce the empty bins in advance.
no code implementations • 8 Apr 2019 • Yong Luo, Yonggang Wen, DaCheng Tao, Jie Gui, Chao Xu
The features used in many image analysis-based applications are frequently of very high dimension.
no code implementations • 7 Apr 2019 • Jie Gui, Tongliang Liu, Zhenan Sun, DaCheng Tao, Tieniu Tan
Rather than adopting this method, FSDH uses a very simple yet effective regression of the class labels of training examples to the corresponding hash code to accelerate the algorithm.
no code implementations • 7 Apr 2019 • Jie Gui, Tongliang Liu, Zhenan Sun, DaCheng Tao, Tieniu Tan
In SDHR, the regression target is instead optimized.