搜索结果: 1-15 共查到“工学 Neural network”相关记录125条 . 查询时间(0.074 秒)
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Barron Type Spaces in Neural Network Approximation
神经网络 巴伦类型空间 经典函数空间
font style='font-size:12px;'>
2023/4/13
We shall discuss various Barron type spaces arising from neural networks. The relations among these spaces will be clarified, and we shall also establish the relationship between Barron type spaces an...
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Deep neural network approximation to inverse conductivity problems for elliptic equations
椭圆方程 反电导率 深度神经网络
font style='font-size:12px;'>
2023/4/14
The focus of this talk is on the numerical methods used to identify parameters in partial differential equations. Typically, an optimization approach is used to solve this class of inverse problems, w...
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：A two-stage physics-informed neural network method based on conserved quantities and applications in localized wave solutions
守恒量 两阶段物理信息 神经网络方法 局部波解
font style='font-size:12px;'>
2023/5/5
With the advantages of fast calculating speed and high precision, the physics-informed neural network method opens up a new approach for numerically solving nonlinear partial differential equations. B...
Packard fellow McMahon rethinks neural-network computing（图）
帕卡德 麦克马洪 神经网络计算
font style='font-size:12px;'>
2023/5/18
Artificial intelligence and machine learning have become crucial tools for medical imaging, autonomous vehicles and many other applications, but engineers warn that the exponential increase in compute...
ORTHOSEG: A DEEP MULTIMODAL CONVOLUTONAL NEURAL NETWORK ARCHITECTURE FOR SEMANTIC SEGMENTATION OF ORTHOIMAGERY
Deep Learning Supervised Image Segmentation Residual Networks
font style='font-size:12px;'>
2019/2/28
This paper addresses the task of semantic segmentation of orthoimagery using multimodal data e.g. optical RGB, infrared and digital surface model. We propose a deep convolutional neural network archit...
ABOVEGROUND BIOMASS ESTIMATION USING RECONSTRUCTED FEATURE OF AIRBORNE DISCRETE-RETURN LIDAR BY AUTO-ENCODER NEURAL NETWORK
Aboveground Biomass (AGB) Estimation Discrete-Return LiDAR Regression Auto-Encoder Neural Network
font style='font-size:12px;'>
2018/5/14
Aboveground biomass (AGB) estimation is critical for quantifying carbon stocks and essential for evaluating carbon cycle. In recent years, airborne LiDAR shows its great ability for highly-precision A...
STUDY ON THE CLASSIFICATION OF GAOFEN-3 POLARIMETRIC SAR IMAGES USING DEEP NEURAL NETWORK
SAR Classification Deep Learning GoogLeNet Landcover Gaofen-3 satellite
font style='font-size:12px;'>
2018/5/16
Polarimetric Synthetic Aperture Radar（POLSAR） imaging principle determines that the image quality will be affected by speckle noise. So the recognition accuracy of traditional image classification met...
DEEP CONVOLUTIONAL NEURAL NETWORK FOR AUTOMATIC DETECTION OF DAMAGED PHOTOVOLTAIC CELLS
UAV, monitoring/inspection Anomaly Detection Deep Learning Photovoltaic Panels Thermography Classification
font style='font-size:12px;'>
2018/6/4
The number of distributed Photovoltaic (PV) plants that produce electricity has been significantly increased, and issue of monitoring and maintaining a PV plant has become of great importance and invo...
THE SEGMENTATION OF POINT CLOUDS WITH K-MEANS AND ANN (ARTIFICAL NEURAL NETWORK)
Lidar Laser Scanning Photogrammetry Segmentation K-means ANN
font style='font-size:12px;'>
2017/7/13
Segmentation of point clouds is recently used in many Geomatics Engineering applications such as the building extraction in urban areas, Digital Terrain Model (DTM) generation and the road or urban fu...
CONVOLUTIONAL NEURAL NETWORK FOR CAMERA POSE ESTIMATION FROM OBJECT DETECTIONS
Camera Pose CNN Head Detection Computer Graphics
font style='font-size:12px;'>
2017/6/19
Known scene geometry and camera calibration parameters give important information to video content analysis systems. In this paper, we propose a novel method for camera pose estimation based on people...
Stanford researchers create a high-performance,low-energy artificial synapse for neural network computing
Stanford researchers high-performance low-energy artificial synapse neural network computing
font style='font-size:12px;'>
2017/3/14
For all the improvements in computer technology over the years, we still struggle to recreate the low-energy, elegant processing of the human brain. Now, researchers at Stanford University and Sandia ...
COSTAL BATHYMETRY ESTIMATION FROM MULTISPECTRAL IMAGE WITH BACK PROPAGATION NEURAL NETWORK
Bathymetry Multispectral Image Stereo Image Back Propagation Neural Network
font style='font-size:12px;'>
2016/12/1
Bathymetric data in coastal area are important for marine sciences, hydrological applications and even for transportation and military purposes. Compare to traditional sonar and recent airborne bathym...
INTERVAL TYPE-2 FUZZY BASED NEURAL NETWORK FOR HIGH RESOLUTION REMOTE SENSING IMAGE SEGMENTATION
Interval Type-2 Fuzzy Model High Resolution Remote Sensing Image Footprint of Uncertainty Image Segmentation Neuron Networks
font style='font-size:12px;'>
2016/11/23
Recently, high resolution remote sensing image segmentation is a hot issue in image procesing procedures. However, it is a difficult task. The difficulties derive from the uncertainties of pixel segme...
BOUNDARY DEPTH INFORMATION USING HOPFIELD NEURAL NETWORK
Boundary Stereo Matching Depth Information Optimization Discontinuity Hopfield Neural Network
font style='font-size:12px;'>
2016/11/11
Depth information is widely used for representation, reconstruction and modeling of 3D scene. Generally two kinds of methods can obtain the depth information. One is to use the distance cues from the ...
IMAGE LABELING FOR LIDAR INTENSITY IMAGE USING K-NN OF FEATURE OBTAINED BY CONVOLUTIONAL NEURAL NETWORK
Image labeling Convolutional neural network K-nearest neighbour and LIDAR intensity image
font style='font-size:12px;'>
2016/7/28
We propose an image labeling method for LIDAR intensity image obtained by Mobile Mapping System (MMS) using K-Nearest Neighbor (KNN) of feature obtained by Convolutional Neural Network (CNN). Image la...