H
Honghai Liu
Researcher at Harbin Institute of Technology
Publications - 544
Citations - 13101
Honghai Liu is an academic researcher from Harbin Institute of Technology. The author has contributed to research in topics: Computer science & Fuzzy logic. The author has an hindex of 47, co-authored 459 publications receiving 10500 citations. Previous affiliations of Honghai Liu include Peking Union Medical College Hospital & Nanjing Forestry University.
Papers
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Book ChapterDOI
Dynamic Grasp Recognition Using Time Clustering, Gaussian Mixture Models and Hidden Markov Models
TL;DR: The state of the art in recognizing continuous grasping gestures of human hands is demonstrated and a novel time clustering method (TC) and modified methods based on Gaussian Mixture Models (GMMs) and Hidden Markov Models (HMMs) individually are proposed.
Journal ArticleDOI
Drying Stress and Strain of Wood: A Review
Qin Yin,Honghai Liu +1 more
TL;DR: Wang et al. as mentioned in this paper summarized the theory and experimental testing methods of drying stress and strain and applied artificial neural networks (ANN) and their application in the wood drying field to solve the problem of defects.
Journal ArticleDOI
Regression-Based Facial Expression Optimization
Hui Yu,Honghai Liu +1 more
TL;DR: An approach for reproducing optimal 3-D facial expressions based on blendshape regression aims to improve fidelity of facial expressions but maintain the efficiency of the blendshape method, which is necessary for applications such as human-machine interaction and avatars.
Proceedings ArticleDOI
Adaptive fuzzy logic controller for vehicle active suspensions with interval type-2 fuzzy membership functions
TL;DR: An adaptive fuzzy logic controller based on interval type-2 fuzzy sets is proposed for vehicle non-linear active suspension systems and significantly outperforms conventional fuzzy controllers of an active suspension and a passive suspension.
Journal ArticleDOI
Improved itracker combined with bidirectional long short-term memory for 3D gaze estimation using appearance cues
Xiaolong Zhou,Jianing Lin,Zhuo Zhang,Zhanpeng Shao,Shen-Yong Chen,Shen-Yong Chen,Honghai Liu +6 more
TL;DR: An improved Itracker to predict the subject’s gaze for a single image frame, as well as employ a many-to-one bidirectional Long Short-Term Memory (bi-LSTM) to fit the temporal information between frames to estimate gaze for video sequence.