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Yonghuai Liu
Researcher at Edge Hill University
Publications - 200
Citations - 3700
Yonghuai Liu is an academic researcher from Edge Hill University. The author has contributed to research in topics: Real image & Image registration. The author has an hindex of 23, co-authored 189 publications receiving 2770 citations. Previous affiliations of Yonghuai Liu include Sainsbury Laboratory & University of Sheffield.
Papers
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Journal ArticleDOI
Registration of 3D Point Clouds and Meshes: A Survey from Rigid to Nonrigid
Gary K. L. Tam,Zhi-Quan Cheng,Yu-Kun Lai,Frank C. Langbein,Yonghuai Liu,David Marshall,Ralph R. Martin,Xianfang Sun,Paul L. Rosin +8 more
TL;DR: This study serves to give a comprehensive survey of both types of registration, focusing on three-dimensional point clouds and meshes, and shows how overfitting arises in nonrigid registration and the reasons for increasing interest in intrinsic techniques.
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Improving ICP with easy implementation for free-form surface matching
TL;DR: This paper proposes a novel practical algorithm that directly manipulates the possible point matches established by the traditional ICP criterion based on both the collinearity and closeness constraints without any feature extraction, image pre-processing, or motion estimation from outliers corrupted data.
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Temporal convolutional neural (TCN) network for an effective weather forecasting using time-series data from the local weather station
Pradeep Ruwan Padmasiri Galbokka Hewage,Ardhendu Behera,Marcello Trovati,Ella Pereira,Morteza Ghahremani,Francesco Palmieri,Yonghuai Liu +6 more
TL;DR: This research aims to address non-predictive or inaccurate weather forecasting by developing and evaluating a lightweight and novel weather forecasting system, which consists of one or more local weather stations and state-of-the-art machine learning techniques for weather forecasting using time-series data from these weather stations.
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Mesh saliency via spectral processing
TL;DR: The benefits of the proposed method are further evaluated in applications such as mesh simplification, mesh segmentation, and scan integration, where it is shown how incorporating mesh saliency can provide improved results.
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Human consistency evaluation of static video summaries
TL;DR: The results show that the level of agreement varies significantly between the users for the selection of key frames, which denotes the hidden challenge in automatic video summary evaluation.