相关参考文献
注意：仅列出部分参考文献，下载原文获取全部文献信息。Segmentation of digital rock images using deep convolutional autoencoder networks
Sadegh Karimpouli et al.
COMPUTERS & GEOSCIENCES (2019)
DepthLearn: Learning to Correct the Refraction on Point Clouds Derived from Aerial Imagery for Accurate Dense Shallow Water Bathymetry Based on SVMs-Fusion with LiDAR Point Clouds
Panagiotis Agrafiotis et al.
REMOTE SENSING (2019)
Bathymetry retrieval from optical images with spatially distributed support vector machines
Lei Wang et al.
GISCIENCE & REMOTE SENSING (2019)
A learning-based data-driven forecast approach for predicting future reservoir performance
Hoonyoung Jeong et al.
ADVANCES IN WATER RESOURCES (2018)
Shallow water bathymetry mapping using Support Vector Machine (SVM) technique and multispectral imagery
Ankita Misra et al.
INTERNATIONAL JOURNAL OF REMOTE SENSING (2018)
Riverine Bathymetry Imaging With Indirect Observations
Jonghyun Lee et al.
WATER RESOURCES RESEARCH (2018)
Bathymetric Structure-from-Motion: extracting shallow stream bathymetry from multi-view stereo photogrammetry
James T. Dietrich
EARTH SURFACE PROCESSES AND LANDFORMS (2017)
Why and When Can Deep-but Not Shallow-networks Avoid the Curse of Dimensionality: A Review
Tomaso Poggio et al.
INTERNATIONAL JOURNAL OF AUTOMATION AND COMPUTING (2017)
Production forecasting and uncertainty quantification for naturally fractured reservoirs using a new data-space inversion procedure
Wenyue Sun et al.
COMPUTATIONAL GEOSCIENCES (2017)
Compressed state Kalman filter for large systems
Peter K. Kitanidis
ADVANCES IN WATER RESOURCES (2015)
Inference of effective river properties from remotely sensed observations of water surface
Pierre-Andre Garambois et al.
ADVANCES IN WATER RESOURCES (2015)
Deep learning in neural networks: An overview
Juergen Schmidhuber
NEURAL NETWORKS (2015)
Bathymetry Estimation Using Drifter-Based Velocity Measurements on the Kootenai River, Idaho
Kyle C. Landon et al.
JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY (2014)
Large-scale hydraulic tomography and joint inversion of head and tracer data using the Principal Component Geostatistical Approach (PCGA)
J. Lee et al.
WATER RESOURCES RESEARCH (2014)
Principal Component Geostatistical Approach for large-dimensional inverse problems
P. K. Kitanidis et al.
WATER RESOURCES RESEARCH (2014)
Remotely Sensed Empirical Modeling of Bathymetry in the Southeastern Caspian Sea
Mehdi Gholamalifard et al.
REMOTE SENSING (2013)
Ensemble-Based Data Assimilation for Estimation of River Depths
Greg Wilson et al.
JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY (2012)
Estimating river bathymetry from data assimilation of synthetic SWOT measurements
Yeosang Yoon et al.
JOURNAL OF HYDROLOGY (2012)
Quantifying riverine surface currents from time sequences of thermal infrared imagery
Jack A. Puleo et al.
WATER RESOURCES RESEARCH (2012)
Approaching bathymetry estimation from high resolution multispectral satellite images using a neuro-fuzzy technique
Linda Corucci et al.
JOURNAL OF APPLIED REMOTE SENSING (2011)
Efficient Implicit Finite-Element Hydrodynamic Model for Dam and Levee Breach
Gaurav Savant et al.
JOURNAL OF HYDRAULIC ENGINEERING (2011)
Remote sensing of water depths in shallow waters via artificial neural networks
Oezcelik Ceyhun et al.
ESTUARINE COASTAL AND SHELF SCIENCE (2010)
Remote Sensing of Channels and Riparian Zones with a Narrow-Beam Aquatic-Terrestrial LIDAR
Jim McKean et al.
REMOTE SENSING (2009)
Learning Deep Architectures for AI
Yoshua Bengio
FOUNDATIONS AND TRENDS IN MACHINE LEARNING (2009)
Assessing the ability of airborne LiDAR to map river bathymetry
Robert C. Hilldale et al.
EARTH SURFACE PROCESSES AND LANDFORMS (2008)
Large-scale particle image velocimetry for measurements in riverine environments
M. Muste et al.
WATER RESOURCES RESEARCH (2008)
The topographic data source of digital terrain models as a key element in the accuracy of hydraulic flood modelling
A Casas et al.
EARTH SURFACE PROCESSES AND LANDFORMS (2006)
分享论文
