Hao Li is a PhD-degree candidate in the Mewbourne College of Earth and Energy (MCEE) at the University of Oklahoma in Norman. He interned with Facebook on improving ranking models using machine learning. His research interests include machine learning, petrophysics, and data analytics. He holds an MS degree in petroleum engineering from China University of Petroleum in Beijing.
4 résultat(s)
Télécharger le livre : Geometry Fundamentals of Computer Vision
Hao Li
Geometry Fundamentals of Computer Vision
This book enables readers to acquire a fundamental knowledge of computer vision from the perspective of geometry, including knowledge of image processing and pattern recognition intended for two-dimensional geometry analysis of images, knowledge of computer vision...
Editeur : Springer
Parution : 2025-10-09

Format(s) : PDF, ePub
220,49 €
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Télécharger le livre : Control Theory for Practical Applications
Hao Li
Control Theory for Practical Applications
This book enables readers to acquire a fundamental knowledge of control theory on classical control, modern control, and advanced control, including representative control methods. From the pedagogic perspective, the author intends that this book helps students to...
Editeur : Springer
Parution : 2024-12-23

Format(s) : PDF, ePub
168,79 €
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Télécharger le livre : Energy Management of Integrated Energy System in Large Ports
Hao Li , Wentao Huang , Hao Li , Nengling Tai , Moduo Yu
Energy Management of Integrated Energy System in Large Ports
This open access book provides a detailed exploration of energy management in seaport integrated energy systems, highlighting their potential to replace conventional fuel-based energy usage and promote sustainable development of large ports. In order to achieve carbon...
Editeur : Springer
Parution : 2023-12-30
Collection : Springer Series on Naval Architecture, Marine Engineering, Shipbuilding and Shipping
Format(s) : PDF, ePub
Gratuit
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Télécharger le livre : Machine Learning for Subsurface Characterization
Hao Li , Jiabo He , Siddharth Misra
Machine Learning for Subsurface Characterization
Machine Learning for Subsurface Characterization develops and applies neural networks, random forests, deep learning, unsupervised learning, Bayesian frameworks, and clustering methods for subsurface characterization.Machine learning (ML) focusses on developing...
Editeur : Gulf Professional Publishing
Parution : 2019-10-12

Format(s) : epub sans DRM
128,71 €
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