Results 31 to 40 of about 175,174 (259)

Bayesian Fusion of Multi-Scale Detectors for Road Extraction from SAR Images

ISPRS International Journal of Geo-Information, 2017
This paper introduces an innovative road network extraction algorithm using synthetic aperture radar (SAR) imagery for improving the accuracy of road extraction.
Rui Xu, Chu He, Xinlong Liu, Dong Chen, Qianqing Qin   +4 more
doaj   +1 more source

DeepWindow: Sliding Window Based on Deep Learning for Road Extraction From Remote Sensing Images

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020
The road centerline extraction is the key step of the road network extraction and modeling. The hand-craft feature engineering in the traditional road extraction methods is unstable, which makes the extracted road centerline deviated from the road center
Renbao Lian, Liqin Huang
doaj   +1 more source

A Model-Driven-to-Sample-Driven Method for Rural Road Extraction

Remote Sensing, 2021
Road extraction in rural areas is one of the most fundamental tasks in the practical application of remote sensing. In recent years, sample-driven methods have achieved state-of-the-art performance in road extraction tasks. However, sample-driven methods
Jiguang Dai, Rongchen Ma, Litao Gong, Zimo Shen, Jialin Wu   +4 more
doaj   +1 more source

Financial Burden Associated With Hospitalisation Among Families of Childhood Brain Tumours in Australia

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Families of children with cancer experience significant financial strain, even with universal healthcare. Indirect costs, such as productivity losses and non‐medical expenses, are rarely included in economic evaluations, and little is known about how effectively financial aid programmes alleviate this burden. Childhood brain tumours
Megumi Lim, Natalie Bradford, David Brain, Sameera Senanayake, Sanjeewa Kularatna, Kate Young, Christine Cashion, Tim Hassall, Susanna Cramb   +8 more
wiley   +1 more source

Forest/rural road network detection and condition monitoring based on satellite imagery and deep semantic segmentation [PDF]

ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Sustainable forest and emergency management require comprehensive data on the forest road network and its condition. This paper presents the final framework of the INFOROAD project (https://inforoad.karteco.gr/), which integrates cutting-edge remote ...
D. Kelesakis, K. Marthoglou, E. Tokmaktsi, E. Tsiros, A. Karteris, A. Stergiadou, G. Kolkos, P. Daras, N. Grammalidis   +8 more
doaj   +1 more source

Semi-Automatic Extraction of Rural Roads under the Constraint of Combined Geometric and Texture Features

ISPRS International Journal of Geo-Information, 2021
The extraction of road information from high-resolution remotely-sensed images has important application value in many fields. Rural roads have the characteristics of relatively narrow widths and diversified pavement materials; these characteristics can ...
Hai Tan, Zimo Shen, Jiguang Dai
doaj   +1 more source

Road Extraction using Deep Learning

International Journal of Engineering & Technology, 2018
The Road extraction from aerial image, stands as a quintessential node for the development of rudimentary layers in innumerable fields. From GIS, to Unmanned Aerial vehicles, road maps pave the foundation for data accumulation. This significant process is a result of number of mechanisms devised over the years through iterative experiments and research.
J. D. Dorathi Jayaseeli, D. Malathi, Gopika S   +2 more
openaire   +2 more sources

The Fate (Outcome) of Clinically Apparent Single Lesion and Oligofocal Nephroblastomatosis Treated According to SIOP/GPOH Protocols for Wilms Tumor

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background The management of clinically apparent single lesions or oligofocal nephroblastomatosis, a facultative precursor of nephroblastoma, remains debated. Methods We retrospectively analyzed 37 patients with clinically apparent single or oligofocal nephroblastomatosis (two to three lesions per kidney) among 2347 patients registered between
Nils Welter, Jens‐Peter Schenk, Jenny Wegert, Manfred Gessler, Leo Kager, Stefan Wagenpfeil, Marina Müller, Jean‐Michel Wolff, Joerg Fuchs, Steven W. Warmann, Clemens‐Magnus Meier, Jochen Hubertus, Christian Rübe, Christian Vokuhl, Patrick Melchior, Lena Tschirner, Norbert Graf, Rhoikos Furtwängler   +17 more
wiley   +1 more source

A Review of Deep Learning-Based Methods for Road Extraction from High-Resolution Remote Sensing Images

Remote Sensing
Road extraction from high-resolution remote sensing images has long been a focal and challenging research topic in the field of computer vision. Accurate extraction of road networks holds extensive practical value in various fields, such as urban ...
Ruyi Liu, Junhong Wu, Wenyi Lu, Qiguang Miao, Huan Zhang, Xiangzeng Liu, Zixiang Lu, Long Li   +7 more
doaj   +1 more source

Reconstruction Bias U-Net for Road Extraction From Optical Remote Sensing Images

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021
Automatic road extraction from remote sensing images plays an important role for navigation, intelligent transportation, and road network update, etc. Convolutional neural network (CNN)-based methods have presented many achievements for road extraction ...
Ziyi Chen, Cheng Wang, Jonathan Li, Nianci Xie, Yan Han, Jixiang Du   +5 more
doaj   +1 more source