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Spectral–Spatial Residual Network for Hyperspectral Image Classification: A 3-D Deep Learning Framework
In this paper, we designed an end-to-end spectral–spatial residual network (SSRN) that takes raw 3-D cubes as input data without feature engineering for hyperspectral image classification. Expand
Using mobile laser scanning data for automated extraction of road markings
Abstract A mobile laser scanning (MLS) system allows direct collection of accurate 3D point information in unprecedented detail at highway speeds and at less than traditional survey costs, whichExpand
An integrated INS/GPS approach to the georeferencing of remotely sensed data
A general model for the georeferencing of remotely sensed data by an onboard positioning and orientation system is presented as a problem of rigid body motion. The determination of the sixExpand
Automated Road Information Extraction From Mobile Laser Scanning Data
This paper presents a survey of literature about road feature extraction, giving a detailed description of a Mobile Laser Scanning (MLS) system (RIEGL VMX-450) for transportation-related applications, and develops automated algorithms for extracting road features (road surfaces, road markings, and pavement cracks) from MLS point cloud data. Expand
Segmentation of SAR Intensity Imagery With a Voronoi Tessellation, Bayesian Inference, and Reversible Jump MCMC Algorithm
This paper presents a region-based approach to segmentation of the satellite synthetic aperture radar (SAR) intensity imagery. Expand
Automated Road Extraction from Satellite Imagery Using Hybrid Genetic Algorithms and Cluster Analysis
This paper presents a new approach to road extraction from high-resolution satellite imagery based on Genetic Algorithms with fitness calculation of clustering. Expand
Semiautomated Segmentation of Sentinel-1 SAR Imagery for Mapping Sea Ice in Labrador Coast
This study aims at proposing a semiautomated sea ice segmentation workflow utilizing Sentinel-1 synthetic aperture radar imagery. Expand
Automated processing of mobile mapping image sequences
This paper presents an overview of several methods developed for the VISAT™ mobile mapping system at The University of Calgary. Expand
Multi-Scale Point-Wise Convolutional Neural Networks for 3D Object Segmentation From LiDAR Point Clouds in Large-Scale Environments
This paper provides an end-to-end feature extraction framework for 3D point cloud segmentation by using dynamic point-wise convolutional operations in multiple scales. Expand
Integration of orthoimagery and lidar data for object-based urban thematic mapping using random forests
Using high-spatial-resolution multispectral imagery alone is insufficient for achieving highly accurate and reliable thematic mapping of urban areas. Expand