Remote sensing object detection in the deep learning era—a review
Given the large volume of remote sensing images collected daily, automatic object detection
and segmentation have been a consistent need in Earth observation (EO). However, objects …
and segmentation have been a consistent need in Earth observation (EO). However, objects …
[HTML][HTML] Cost-efficient information extraction from massive remote sensing data: When weakly supervised deep learning meets remote sensing big data
With many platforms and sensors continuously observing the earth surface, the large
amount of remote sensing data presents a big data challenge. While remote sensing data …
amount of remote sensing data presents a big data challenge. While remote sensing data …
Review of deep learning methods for remote sensing satellite images classification: experimental survey and comparative analysis
Classification and analysis of high-resolution satellite images using conventional techniques
have been limited. This is due to the complex characteristics of the imagery. These images …
have been limited. This is due to the complex characteristics of the imagery. These images …
HiSup: Accurate polygonal mapping of buildings in satellite imagery with hierarchical supervision
This paper studies the problem of the polygonal mapping of buildings by tackling the issue
of mask reversibility, which leads to a notable performance gap between the predicted …
of mask reversibility, which leads to a notable performance gap between the predicted …
Holistically-attracted wireframe parsing: From supervised to self-supervised learning
This article presents Holistically-Attracted Wireframe Parsing (HAWP), a method for
geometric analysis of 2D images containing wireframes formed by line segments and …
geometric analysis of 2D images containing wireframes formed by line segments and …
A deep learning classification approach using high spatial satellite images for detection of built-up areas in rural zones: Case study of Souss-Massa region-Morocco
M Wahbi, I El Bakali, B Ez-zahouani, R Azmi… - Remote Sensing …, 2023 - Elsevier
The buildings in the rural areas of Morocco exist in various shapes and sizes. They are
randomly distributed and are generally constructed of primary materials such as clay, wood …
randomly distributed and are generally constructed of primary materials such as clay, wood …
Deep semantic segmentation of trees using multispectral images
Forests can be efficiently monitored by automatic semantic segmentation of trees using
satellite and/or aerial images. Still, several challenges can make the problem difficult …
satellite and/or aerial images. Still, several challenges can make the problem difficult …
Improving building rooftop segmentation accuracy through the optimization of UNet basic elements and image foreground-background balance
J Yang, B Matsushita, H Zhang - ISPRS Journal of Photogrammetry and …, 2023 - Elsevier
Building rooftop segmentation using deep learning techniques is a popular yet challenging
area of research in computer vision and remote sensing image processing. While recent …
area of research in computer vision and remote sensing image processing. While recent …
Skin lesion classification based on surface fractal dimensions and statistical color cluster features using an ensemble of machine learning techniques
S Moldovanu, FA Damian Michis, KC Biswas… - Cancers, 2021 - mdpi.com
Simple Summary This study aimed to investigate the efficacy of implementation of novel skin
surface fractal dimension features as an auxiliary diagnostic method for melanoma …
surface fractal dimension features as an auxiliary diagnostic method for melanoma …
Earth observation mission of a 6U CubeSat with a 5-meter resolution for wildfire image classification using convolution neural network approach
The KITSUNE satellite is a 6-unit CubeSat platform with the main mission of 5-m-class Earth
observation in low Earth orbit (LEO), and the payload is developed with a 31.4 MP …
observation in low Earth orbit (LEO), and the payload is developed with a 31.4 MP …