A review of deep learning methods for semantic segmentation of remote sensing imagery
X Yuan, J Shi, L Gu - Expert Systems with Applications, 2021 - Elsevier
Semantic segmentation of remote sensing imagery has been employed in many
applications and is a key research topic for decades. With the success of deep learning …
applications and is a key research topic for decades. With the success of deep learning …
[HTML][HTML] Road extraction in remote sensing data: A survey
Automated extraction of roads from remotely sensed data come forth various usages ranging
from digital twins for smart cities, intelligent transportation, urban planning, autonomous …
from digital twins for smart cities, intelligent transportation, urban planning, autonomous …
Creating xBD: A dataset for assessing building damage from satellite imagery
We present a preliminary report for xBD, a new large-scale dataset for the advancement of
change detection and building damage assessment for humanitarian assistance and …
change detection and building damage assessment for humanitarian assistance and …
Deep learning approaches applied to remote sensing datasets for road extraction: A state-of-the-art review
One of the most challenging research subjects in remote sensing is feature extraction, such
as road features, from remote sensing images. Such an extraction influences multiple …
as road features, from remote sensing images. Such an extraction influences multiple …
Object detection and image segmentation with deep learning on Earth observation data: A review—Part II: Applications
In Earth observation (EO), large-scale land-surface dynamics are traditionally analyzed by
investigating aggregated classes. The increase in data with a very high spatial resolution …
investigating aggregated classes. The increase in data with a very high spatial resolution …
Weakly supervised deep learning for segmentation of remote sensing imagery
Accurate automated segmentation of remote sensing data could benefit applications from
land cover mapping and agricultural monitoring to urban development surveyal and disaster …
land cover mapping and agricultural monitoring to urban development surveyal and disaster …
Road segmentation for remote sensing images using adversarial spatial pyramid networks
Road extraction in remote sensing images is of great importance for a wide range of
applications. Because of the complex background, and high density, most of the existing …
applications. Because of the complex background, and high density, most of the existing …
Sar-to-optical image translation based on conditional generative adversarial networks—Optimization, opportunities and limits
Due to its all time capability, synthetic aperture radar (SAR) remote sensing plays an
important role in Earth observation. The ability to interpret the data is limited, even for …
important role in Earth observation. The ability to interpret the data is limited, even for …
Semantic segmentation and edge detection—Approach to road detection in very high resolution satellite images
Road detection technology plays an essential role in a variety of applications, such as urban
planning, map updating, traffic monitoring and automatic vehicle navigation. Recently, there …
planning, map updating, traffic monitoring and automatic vehicle navigation. Recently, there …
Index your position: A novel self-supervised learning method for remote sensing images semantic segmentation
Learning effective visual representations without human supervision is a critical problem for
the task of semantic segmentation of remote sensing images (RSIs), where pixel-level …
the task of semantic segmentation of remote sensing images (RSIs), where pixel-level …