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Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：VC-PINN: variable coefficient physics-informed neural network for forward and inverse problems of PDEs with variable coefficient
VC-PINN 变系数 偏微分方程 正逆问题 变系数物理 知情神经网络
2023/11/13
The talk proposes a deep learning method specifically dealing with the forward and inverse problem of variable coefficient partial differential equations-Variable Coefficient Physics-Informed Neural N...
COMPARATIVE STUDY ON DEEP NEURAL NETWORK MODELS FOR CROP CLASSIFICATION USING TIME SERIES POLSAR AND OPTICAL DATA
Deep neural networks CNNs LSTMs ConvLSTMs Crop classification
2019/2/28
Crop classification is an important task in many crop monitoring applications. Satellite remote sensing has provided easy, reliable, and fast approaches to crop classification task. In this study, a c...
SPECTRAL-SPATIAL CLASSIFICATION OF HYPERSPECTRAL REMOTE SENSING IMAGES USING VARIATIONAL AUTOENCODER AND CONVOLUTION NEURAL NETWORK
Hyperspectral classification feature extraction spectral channels deep learning
2019/2/28
In this paper, we propose a spectral-spatial feature extraction framework based on deep learning (DL) for hyperspectral image (HSI) classification. In this framework, the variational autoencoder (VAE)...
MULTISPECTRAL PANSHARPENING APPROACH USING PULSE-COUPLED NEURAL NETWORK SEGMENTATION
Pansharpening PCNN Image Fusion Multispectral Imaging Remote Sensing Segmentation
2018/5/14
The paper proposes a novel pansharpening method based on the pulse-coupled neural network segmentation. In the new method, uniform injection gains of each region are estimated through PCNN segmentatio...
A NOVEL DEEP CONVOLUTIONAL NEURAL NETWORK FOR SPECTRAL–SPATIAL CLASSIFICATION OF HYPERSPECTRAL DATA
Hyperspectral Data Classification Three-dimensional Convolution Deep CNN Feature Extraction
2018/5/14
Spatial and spectral information are obtained simultaneously by hyperspectral remote sensing. Joint extraction of these information of hyperspectral image is one of most import methods for hyperspectr...
THE EXTRACTION OF POST-EARTHQUAKE BUILDING DAMAGE INFORMATIOM BASED ON CONVOLUTIONAL NEURAL NETWORK
Earthquake Seismic Damage Information Extraction Deep Learning Convolutional Neural Network
2018/5/11
The seismic damage information of buildings extracted from remote sensing (RS) imagery is meaningful for supporting relief and effective reduction of losses caused by earthquake. Both traditional pixe...
RESEARCH ON THE DIRECT CARBON EMISSION FORECAST OF CHINA'S PROVINCIAL RESIDENTS BASED ON NEURAL NETWORK
Global climate change Residents’ carbon emissions Elman Neural network Forecast China
2018/5/16
Global climate change, which mainly effected by human carbon emissions, would affect the regional economic, natural ecological environment, social development and food security in the near future. It’...
SEMANTIC SEGMENTATION OF CONVOLUTIONAL NEURAL NETWORK FOR SUPERVISED CLASSIFICATION OF MULTISPECTRAL REMOTE SENSING
Semantic Segmentation Multi Spectral Remote Sensing Convolutional Neural Network U-net multi-scale image
2018/5/16
Semantic segmentation is a fundamental research in remote sensing image processing. Because of the complex maritime environment, the classification of roads, vegetation, buildings and water from remot...
EIGENENTROPY BASED CONVOLUTIONAL NEURAL NETWORK BASED ALS POINT CLOUDS CLASSIFICATION METHOD
EIGENENTROPY CONVOLUTIONAL NEURAL NETWORK ALS POINT CLOUDS CLASSIFICATION METHOD
2018/5/16
The classification of point clouds is the first step in the extraction of various types of geo-information form point clouds. Recently the ISPRS WG II/4 provides a benchmark on 3D semantic labelling, ...
A new approach for residual gravity anomaly profile interpretations: Forced Neural Network (FNN)
Forced Neural Network gravity anomaly modeling synthetic model Gulf of Mexico
2015/9/8
This paper presents a new approach for interpretation of residual gravity anomaly profiles, assuming horizontal
cylinders as source. The new method, called Forced Neural Network (FNN), is introduced ...
Overexpression of a Hyperpolarization-Activated Cation Current (Ih) Channel Gene Modifies the Firing Activity of Identified Motor Neurons in a Small Neural Network
gene expression neuronal network
2015/8/25
Artificial Neural Network Application on Estimation of Aquifer Transmissivity
Aquifer Parameter Feed Forward Back Propagation
2015/8/13
The present study focuses on the unexplored area of application of artificial neural network in groundwater hydrology. Three models, each based on artificial neural networks, are applied for predictio...
Application of an artificial neural network to estimate groundwater level fluctuation
groundwater level fluctuation estimating artificial neural network back propagation algorithms radial basis function MATLAB
2015/8/13
This paper examines and compares the capability of an artificial neural network (ANN) with five different backpropagation (BP) algorithms, namely Gradient descent with momentum (GDM), Gradient descent...
Estimation of Aquifer Transmissivity using Kriging, Artificial Neural Network, and Neuro-Fuzzy models
ransmissivity Kriging Artificial Neural Network ANFIS Neuro-Fuzzy interpolation groundwater
2015/8/11
In interpolation of groundwater properties such as transmissivity, due to the unknown distributed values of the variables and heterogenity, the best and the unbiased aspects are frequently difficult t...
Artificial Neural Network Application on Estimation of Aquifer Transmissivity
Aquifer Parameter Feed Forward Back Propagation Radial Basis Function Recurrent Artificial Neural Network Inverse Modeling Finite Element Method
2015/1/7
The present study focuses on the unexplored area of application of artificial neural network in groundwater hydrology. Three models, each based on artificial neural networks, are applied for predictio...