Houxiang Zhang
Norwegian University of Science and Technology
255 Papers
809 Citations
Houxiang Zhang is an academic researcher from Norwegian University of Science and Technology. The author has contributed to research in topics: Computer science & Robot. The author has an hindex of 24, co-authored 221 publications. Previous affiliations of Houxiang Zhang include University of Hamburg & Beihang University.
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Papers
Remaining useful life predictions for turbofan engine degradation using semi-supervised deep architecture
TL;DR: The results suggest that unsupervised pre-training is a promising feature in RUL predictions subjected to multiple operating conditions and fault modes.
463
Sky Cleaner 3: a real pneumatic climbing robot for glass-wall cleaning
TL;DR: Application of a type of cleaning robotic system can free workers from this hazardous work and realize an automatic cleaning of high-rise buildings, thereby improving the technological level and productivity of the service industry.
175
Three-dimensional point cloud plane segmentation in both structured and unstructured environments
TL;DR: These algorithms have been evaluated using real-world datasets from both structured and unstructured environments and benchmarked against a state-of-the-art point-based region growing (PBRG) algorithm with regard to segmentation speed.
114
A Comprehensive Survey of Prognostics and Health Management Based on Deep Learning for Autonomous Ships
TL;DR: This paper introduces and reviews four well-established DL techniques recently applied to various practical PHM problems and provides inspiration toward the PHM based on DL in autoships and the maritime industry.
97
A Hybrid Approach to Motion Prediction for Ship Docking—Integration of a Neural Network Model Into the Ship Dynamic Model
TL;DR: A tool for onboard support that offers position predictions based on an integration of a supervised machine learning model of the ship into the ship dynamic model is proposed and shows that the inclusion of the data-based ML model significantly improves the prediction accuracy.