22 citations · 57 across the 11 of their papers we have counts for
6 papers · 1 filter
A Robust and Efficient Boundary Point Detection Method by Measuring Local Direction Dispersion
Dehua Peng, Zhipeng Gui, Jie Gui +1
Boundary point detection aims to outline the external contour structure of clusters and enhance the inter-cluster discrimination, thus bolstering the performance of the downstream…
Illumination Controllable Dehazing Network based on Unsupervised Retinex Embedding
Jie Gui, Xiaofeng Cong, Lei He +2
On the one hand, the dehazing task is an illposedness problem, which means that no unique solution exists. On the other hand, the dehazing task should take into account the subject…
No Place to Hide: Dual Deep Interaction Channel Network for Fake News Detection based on Data Augmentation
Biwei Cao, Lulu Hua, Jiuxin Cao +3
Online Social Network (OSN) has become a hotbed of fake news due to the low cost of information dissemination. Although the existing methods have made many attempts in news content…
Fooling the Image Dehazing Models by First Order Gradient
Jie Gui, Xiaofeng Cong, Chengwei Peng +2
The research on the single image dehazing task has been widely explored. However, as far as we know, no comprehensive study has been conducted on the robustness of the well-trained…
A Survey on Self-supervised Learning: Algorithms, Applications, and Future Trends
Jie Gui, Tuo Chen, Jing Zhang +4
Deep supervised learning algorithms typically require a large volume of labeled data to achieve satisfactory performance. However, the process of collecting and labeling such data…
Learning the Relation between Similarity Loss and Clustering Loss in Self-Supervised Learning
Jidong Ge, Yuxiang Liu, Jie Gui +5
Self-supervised learning enables networks to learn discriminative features from massive data itself. Most state-of-the-art methods maximize the similarity between two augmentations…