搜索结果: 1-15 共查到“测绘科学技术 Networks”相关记录87条 . 查询时间(0.205 秒)
BUILDING CLASSIFICATION OF VHR AIRBORNE STEREO IMAGES USING FULLY CONVOLUTIONAL NETWORKS AND FREE TRAINING SAMPLES
Building Classification VHR Airborne Stereo Images FCN Base Map Mislabels Free Training Samples Fine Tuning Atrous Convolution
font style='font-size:12px;'>
2018/11/9
Semantic segmentation, especially for buildings, from the very high resolution (VHR) airborne images is an important task in urban mapping applications. Nowadays, the deep learning has significantly i...
EXPLORING SCHEMA MATCHING TO COMPARE GEOSPATIAL STANDARDS: APPLICATION TO UNDERGROUND UTILITY NETWORKS
Schema matching geospatial standard underground utility network
font style='font-size:12px;'>
2018/11/9
This paper proposes a preliminary analysis of whether a schema matching approach can be applied for the comparison and possible the selection of geospatial standards. Schema matching is tested in the ...
CHANGE DETECTION IN REMOTE SENSING IMAGES USING CONDITIONAL ADVERSARIAL NETWORKS
Change Detection Database Deep Convolutional Neural Networks Generative Adversarial Networks
font style='font-size:12px;'>
2018/6/4
We present a method for change detection in images using Conditional Adversarial Network approach. The original network architecture based on pix2pix is proposed and evaluated for difference map creat...
MULTI-TEMPORAL LAND COVER CLASSIFICATION WITH LONG SHORT-TERM MEMORY NEURAL NETWORKS
Long Short-Term Memory Recurrent Neural Networks Sentinel 2 Crop Identification Deep Learning Land Cover Classification
font style='font-size:12px;'>
2017/7/13
Land cover classification (LCC) is a central and wide field of research in earth observation and has already put forth a variety of classification techniques. Many approaches are based on classificati...
BUILDING EXTRACTION FROM REMOTE SENSING DATA USING FULLY CONVOLUTIONAL NETWORKS
deep learning DSM fully convolutional networks building footprint binary classification fully connected CRF
font style='font-size:12px;'>
2017/7/13
Building detection and footprint extraction are highly demanded for many remote sensing applications. Though most previous works have shown promising results, the automatic extraction of building foot...
Learning Oriented Region-based Convolutional Neural Networks for Building Detection in Satellite Remote Sensing Images
VGG Building detection Deep learning OR-CNN Satellite remote sensing images
font style='font-size:12px;'>
2017/7/13
The automated building detection in aerial images is a fundamental problem encountered in aerial and satellite images analysis. Recently, thanks to the advances in feature descriptions, Region-based C...
CLASSIFICATION OF URBAN AERIAL DATA BASED ON PIXEL LABELLING WITH DEEP CONVOLUTIONAL NEURAL NETWORKS AND LOGISTIC REGRESSION
aerial data urban areas evidence combination object classification deep feature learning
font style='font-size:12px;'>
2016/11/23
The recent success of deep convolutional neural networks (CNN) on a large number of applications can be attributed to large amounts of available training data and increasing computing power. In this p...
EVALUATING THE INITIALIZATION METHODS OF WAVELET NETWORKS FOR HYPERSPECTRAL IMAGE CLASSIFICATION
Hyperspectral Classification Wavelet Neural Networks Wavelet Networks Initialization
font style='font-size:12px;'>
2016/11/23
The idea of using artificial neural network has been proven useful for hyperspectral image classification. However, the high dimensionality of hyperspectral images usually leads to the failure of cons...
FINE REGISTRATION OF KILO-STATION NETWORKS - A MODERN PROCEDURE FOR TERRESTRIAL LASER SCANNING DATA SETS
Registration Terrestrial laser scanners 3D-Network Graph Spectral analysis
font style='font-size:12px;'>
2016/11/11
We propose a complete methodology for the fine registration and referencing of kilo-station networks of terrestrial laser scanner data currently used for many valuable purposes such as 3D as-built rec...
KNOWLEDGE BASED 3D BUILDING MODEL RECOGNITION USING CONVOLUTIONAL NEURAL NETWORKS FROM LIDAR AND AERIAL IMAGERIES
Deep Learning Convolutional Neural Network Pattern Recognition LiDAR 3D Building Model
font style='font-size:12px;'>
2016/7/28
In recent years, with the development of the high resolution data acquisition technologies, many different approaches and algorithms have been presented to extract the accurate and timely updated 3D m...
SINGLE-IMAGE SUPER RESOLUTION FOR MULTISPECTRAL REMOTE SENSING DATA USING CONVOLUTIONAL NEURAL NETWORKS
Single-Image Super Resolution Deep Learning Convolutional Neural Networks Sentinel-2
font style='font-size:12px;'>
2016/7/28
In optical remote sensing, spatial resolution of images is crucial for numerous applications. Space-borne systems are most likely to be affected by a lack of spatial resolution, due to their natural d...
A MODIFIED GENETIC ALGORITHM FOR FINDING FUZZY SHORTEST PATHS IN UNCERTAIN NETWORKS
Genetic Algorithm Shortest Path Problem Uncertainty
font style='font-size:12px;'>
2016/7/8
In realistic network analysis, there are several uncertainties in the measurements and computation of the arcs and vertices. These uncertainties should also be considered in realizing the shortest pat...
HOW TRAVEL DEMAND AFFECTS DETECTION OF NON-RECURRENT TRAFFIC CONGESTION ON URBAN ROAD NETWORKS
Non-recurrent congestion space-time clustering space-time scan statistics
font style='font-size:12px;'>
2016/7/8
Occurrence of non-recurrent traffic congestion hinders the economic activity of a city, as travellers could miss appointments or be late for work or important meetings. Similarly, for shippers, unexpe...
COMPARATIVE RESEARCHES ON PROBABILISTIC NEURAL NETWORKS AND MULTI-LAYER PERCEPTRON NETWORKS FOR REMOTE SENSING IMAGE SEGMENTATION
Remote sensing Segmentation Probabilistic Neural Networks (PNNs) Multi-Layer Perception Networks (MLPNs)
font style='font-size:12px;'>
2016/3/17
Image segmentation is one of the most important methods for extracting information of interest from remote sensing image data, but it still remains some problems, leading to low quality segmentation. ...
Classification of Polarimetric SAR Data by Complex Valued Neural Networks
PolSAR classification machine learning complex valued neural networks
font style='font-size:12px;'>
2016/1/25
In the last decades it often has been shown that Multilayer Perceptrons (MLPs) are powerful function approximators. They were
successfully applied to a lot of different classification problems. Howev...