M. Chapman

Publications68
h-index19
Citations1,544
Highly Influential Citations102
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Spectral–Spatial Residual Network for Hyperspectral Image Classification: A 3-D Deep Learning Framework
TLDR
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, which… Expand
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 six… Expand
Automated Road Information Extraction From Mobile Laser Scanning Data
TLDR
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
TLDR
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
TLDR
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
TLDR
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
TLDR
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
TLDR
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
TLDR
Using high-spatial-resolution multispectral imagery alone is insufficient for achieving highly accurate and reliable thematic mapping of urban areas. Expand
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