Shihao Yuan
Ludwig Maximilian University of Munich
21 Papers
12 Citations
Shihao Yuan is an academic researcher from Ludwig Maximilian University of Munich. The author has contributed to research in topics: Seismometer & Geology. The author has an hindex of 5, co-authored 12 publications. Previous affiliations of Shihao Yuan include Institut de Physique du Globe de Paris.
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Papers
Seismological Processing of Six Degree-of-Freedom Ground-Motion Data.
David Sollberger,Heiner Igel,Cedric Schmelzbach,Pascal Edme,Dirk-Jan van Manen,Felix Bernauer,Shihao Yuan,Joachim Wassermann,Ulrich Schreiber,Johan O. A. Robertsson +9 more
TL;DR: The first-ever 6DOF processing example of a teleseismic earthquake recorded on a multicomponent ring laser observatory is provided and wave parameters and wave types of multiple phases can be automatically estimated using single-station 6DOf processing tools.
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Six Degree‐of‐Freedom Broadband Ground‐Motion Observations with Portable Sensors: Validation, Local Earthquakes, and Signal Processing
Shihao Yuan,Andreino Simonelli,Andreino Simonelli,Chin-Jen Lin,Felix Bernauer,Stefanie Donner,Stefanie Donner,Thomas Braun,Joachim Wassermann,Heiner Igel +9 more
TL;DR: In this paper, the authors present field observations of the first commercial portable broadband rotation sensor specifically designed for seismology, which is a three-component fiber-optic gyro strictly sensitive to ground rotation only.
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Performance Comparison of Feature Detectors on Various Layers of Underwater Acoustic Imagery
TL;DR: In this article , the authors compared the performance of well-established handcrafted feature detectors and that of the increasingly popular deep-learning-based detectors to fill the gap in the literature and found that the ORB (Oriented FAST and Rotated BRIEF) and BRISK (Binary Robust Invariant Scalable Keypoints) detectors achieved the best overall performance, the FAST detector is the fastest, and the PC and Sobel layers are the most favorable for implementing feature detection.