1 code implementation • 30 May 2022 • Luyang Li, Ligang He, Jinjin Gao, Xie Han
PSNet achieves grouping and sampling at the same time while the existing methods process sampling and grouping in two separate steps (such as using FPS plus kNN).
1 code implementation • 29 Mar 2022 • Xufeng Lin, Chang-Tsun Li, Scott Adams, Abbas Kouzani, Richard Jiang, Ligang He, Yongjian Hu, Michael Vernon, Egan Doeven, Lawrence Webb, Todd Mcclellan, Adam Guskic
As an essential prerequisite task in image-based plant phenotyping, leaf segmentation has garnered increasing attention in recent years.
no code implementations • 14 Sep 2021 • Wentai Wu, Ligang He, Weiwei Lin
Both classification and regression tasks are susceptible to the biased distribution of training data.
1 code implementation • 2 Feb 2021 • Wentai Wu, Ligang He, Weiwei Lin, Carsten Maple
The results show that the selective behaviour of our algorithm leads to a significant reduction in the number of communication rounds and the amount of time (up to 2. 4x speedup) for the global model to converge and also provides accuracy gain.
no code implementations • 3 Nov 2020 • Tiansheng Huang, Weiwei Lin, Wentai Wu, Ligang He, Keqin Li, Albert Y. Zomaya
The client selection policy is critical to an FL process in terms of training efficiency, the final model's quality as well as fairness.
no code implementations • 28 Jul 2020 • Wentai Wu, Ligang He, Weiwei Lin, Rui Mao
In this paper, a multi-layer federated learning protocol called HybridFL is designed for the MEC architecture.
no code implementations • 3 Oct 2019 • Wentai Wu, Ligang He, Weiwei Lin, Rui Mao, Carsten Maple, Stephen Jarvis
Federated learning (FL) has attracted increasing attention as a promising approach to driving a vast number of end devices with artificial intelligence.
no code implementations • 3 Aug 2019 • Wentai Wu, Ligang He, Weiwei Lin, Yi Su, Yuhua Cui, Carsten Maple, Stephen Jarvis
In light of this, we have developed a prediction-driven, unsupervised anomaly detection scheme, which adopts a backbone model combining the decomposition and the inference of time series data.