no code implementations • 12 Nov 2023 • Shouhua Zhang, Jiehan Zhou, Xue Ma, Chenglin Wen, Susanna Pirttikangas, Chen Yu, Weishan Zhang, Chunsheng Yang
Traditional fault diagnosis methods using Convolutional Neural Networks (CNNs) face limitations in capturing temporal features (i. e., the variation of vibration signals over time).
no code implementations • 22 Aug 2023 • Zengxiang Li, Zhaoxiang Hou, Hui Liu, Ying Wang, Tongzhi Li, Longfei Xie, Chao Shi, Chengyi Yang, Weishan Zhang, Zelei Liu, Liang Xu
Preliminary experiments show that enterprises can enhance and accumulate intelligent capabilities through multimodal model federated learning, thereby jointly creating an smart city model that provides high-quality intelligent services covering energy infrastructure safety, residential community security, and urban operation management.
no code implementations • 25 Jul 2023 • Leiming Chen, Weishan Zhang, Cihao Dong, Sibo Qiao, Ziling Huang, Yuming Nie, Zhaoxiang Hou, Chee Wei Tan
Traditional federated learning uses the number of samples to calculate the weights of each client model and uses this fixed weight value to fusion the global model.
no code implementations • 24 May 2023 • Hong Wang, Su Yang, Xiaoke Huang, Weishan Zhang
Token filtering to reduce irrelevant tokens prior to self-attention is a straightforward way to enable efficient vision Transformer.
1 code implementation • CVPR 2023 • Wuyang Luo, Su Yang, Xinjian Zhang, Weishan Zhang
Moreover, to produce high-quality edited images, we propose some innovative designs, including Semantic-Aware Self-Propagation Module, Boundary-Anchored Patch Discriminator, and Style-Diversity Object Generator, and integrate them into SIEDOB.
2 code implementations • 13 Mar 2023 • Wuyang Luo, Su Yang, Weishan Zhang
To introduce strong control for face inpainting, we propose a novel reference-guided face inpainting method that fills the large-scale missing region with identity and texture control guided by a reference face image.
1 code implementation • 13 Jul 2022 • Wuyang Luo, Su Yang, Hong Wang, Bo Long, Weishan Zhang
Semantic image editing utilizes local semantic label maps to generate the desired content in the edited region.
no code implementations • 3 Feb 2022 • Peiying Zhang, Chao Wang, Neeraj Kumar, Weishan Zhang, Lei Liu
Simulation experiments verified that the dynamic VNE algorithm based on RL and GCNN has good basic VNE characteristics.
no code implementations • 26 Jan 2022 • Jiaqi Kang, Su Yang, Weishan Zhang
Non-contact facial video-based heart rate estimation using remote photoplethysmography (rPPG) has shown great potential in many applications (e. g., remote health care) and achieved creditable results in constrained scenarios.
no code implementations • 29 Dec 2021 • Bingyang Chen, Tao Chen, Xingjie Zeng, Weishan Zhang, Qinghua Lu, Zhaoxiang Hou, Jiehan Zhou, Sumi Helal
Additionally, a dynamic-weight based fusion strategy is proposed to further improve the accuracy of federated learning, which dynamically selects clients based on the accuracy of each local model.
no code implementations • 29 Dec 2021 • Bingyang Chena, Xingjie Zenga, Weishan Zhang
In this paper, we address this limitation by proposing a dynamic fusion-based federated learning(FL) for OWL identification.
no code implementations • 28 Nov 2021 • Fuxun Yu, Weishan Zhang, Zhuwei Qin, Zirui Xu, Di Wang, ChenChen Liu, Zhi Tian, Xiang Chen
Federated learning learns from scattered data by fusing collaborative models from local nodes.
no code implementations • 10 May 2021 • Hongyong Wang, Xinjian Zhang, Su Yang, Weishan Zhang
The normality-granted optical flow is predicted from a single frame, to keep the motion knowledge focused on normal patterns.
no code implementations • 21 Apr 2021 • Jiehan Zhou, Shouhua Zhang, Qinghua Lu, Wenbin Dai, Min Chen, Xin Liu, Susanna Pirttikangas, Yang Shi, Weishan Zhang, Enrique Herrera-Viedma
Federated learning (FL) brings collaborative intelligence into industries without centralized training data to accelerate the process of Industry 4. 0 on the edge computing level.
no code implementations • 17 Mar 2021 • Wenxi Wang, Huansheng Ning, Feifei Shi, Sahraoui Dhelim, Weishan Zhang, Liming Chen
In particular with the boom of artificial intelligence (AI), social computing is significantly influenced by AI.
no code implementations • 21 Feb 2021 • Wenshan Wang, Su Yang, Weishan Zhang
Predicting risk map of traffic accidents is vital for accident prevention and early planning of emergency response.
no code implementations • 22 Sep 2020 • Weishan Zhang, Tao Zhou, Qinghua Lu, Xiao Wang, Chunsheng Zhu, Haoyun Sun, Zhipeng Wang, Sin Kit Lo, Fei-Yue Wang
To improve communication efficiency and model performance, in this paper, we propose a novel dynamic fusion-based federated learning approach for medical diagnostic image analysis to detect COVID-19 infections.
no code implementations • 6 Sep 2020 • Weishan Zhang, Qinghua Lu, Qiuyu Yu, Zhaotong Li, Yue Liu, Sin Kit Lo, Shiping Chen, Xiwei Xu, Liming Zhu
Therefore, in this paper, we present a platform architecture of blockchain-based federated learning systems for failure detection in IIoT.
no code implementations • 15 Aug 2020 • Fuxun Yu, Weishan Zhang, Zhuwei Qin, Zirui Xu, Di Wang, ChenChen Liu, Zhi Tian, Xiang Chen
Specifically, we design a feature-oriented regulation method ({$\Psi$-Net}) to ensure explicit feature information allocation in different neural network structures.
no code implementations • 27 May 2018 • Xinfeng Zhang, Su Yang, Xinjian Zhang, Weishan Zhang, Jiulong Zhang
In crowded scenes, detection and localization of abnormal behaviors is challenging in that high-density people make object segmentation and tracking extremely difficult.
no code implementations • 28 Feb 2018 • Wenshan Wang, Su Yang, Weishan Zhang, Jiulong Zhang
Through multi-task learning, the proposed models can rate aesthetic images as well as produce comments in an end-to-end manner.