Learning aerial image segmentation from online maps
This paper deals with semantic segmentation of high-resolution (aerial) images where a
semantic class label is assigned to each pixel via supervised classification as a basis for …
semantic class label is assigned to each pixel via supervised classification as a basis for …
Fully convolutional networks for dense semantic labelling of high-resolution aerial imagery
J Sherrah - arXiv preprint arXiv:1606.02585, 2016 - arxiv.org
The trend towards higher resolution remote sensing imagery facilitates a transition from land-
use classification to object-level scene understanding. Rather than relying purely on spectral …
use classification to object-level scene understanding. Rather than relying purely on spectral …
Effective semantic pixel labelling with convolutional networks and conditional random fields
Large amounts of available training data and increasing computing power have led to the
recent success of deep convolutional neural networks (CNN) on a large number of …
recent success of deep convolutional neural networks (CNN) on a large number of …
Semantic labeling of aerial and satellite imagery
Inspired by the recent success of deep convolutional neural networks (CNNs) and feature
aggregation in the field of computer vision and machine learning, we propose an effective …
aggregation in the field of computer vision and machine learning, we propose an effective …
Oblique photogrammetry supporting 3D urban reconstruction of complex scenarios
Accurate 3D city models represent an important source of geospatial information to support
various “smart city” applications, such as space management, energy assessment, 3D …
various “smart city” applications, such as space management, energy assessment, 3D …
Building detection using enhanced HOG–LBP features and region refinement processes
Building detection from two-dimensional high-resolution satellite images is a computer
vision, photogrammetry, and remote sensing task that has arisen in the last decades with the …
vision, photogrammetry, and remote sensing task that has arisen in the last decades with the …
3D building reconstruction from ALS data using unambiguous decomposition into elementary structures
M Jarząbek-Rychard, A Borkowski - ISPRS journal of photogrammetry and …, 2016 - Elsevier
The objective of the paper is to develop an automated method that enables for the
recognition and semantic interpretation of topological building structures. The novelty of the …
recognition and semantic interpretation of topological building structures. The novelty of the …
Geospatial data processing for 3D city model generation, management and visualization
I Toschi, E Nocerino… - … Archives of the …, 2017 - isprs-archives.copernicus.org
Recent developments of 3D technologies and tools have increased availability and
relevance of 3D data (from 3D points to complete city models) in the geospatial and geo …
relevance of 3D data (from 3D points to complete city models) in the geospatial and geo …
Combining high-resolution optical and InSAR features for height estimation of buildings with flat roofs
In this paper, we contribute to answer the question: How accurately can we estimate heights
of buildings with flat roofs given one high-resolution single-pass interferometric synthetic …
of buildings with flat roofs given one high-resolution single-pass interferometric synthetic …
Semantic segmentation of remote sensing image based on convolutional neural network and mask generation
B Niu - Mathematical Problems in Engineering, 2021 - Wiley Online Library
High‐resolution remote sensing images usually contain complex semantic information and
confusing targets, so their semantic segmentation is an important and challenging task. To …
confusing targets, so their semantic segmentation is an important and challenging task. To …