Mapping roads in the Brazilian Amazon with artificial intelligence and Sentinel-2

J Botelho Jr, SCP Costa, JG Ribeiro, CM Souza Jr - Remote Sensing, 2022 - mdpi.com
This study presents our efforts to automate the detection of unofficial roads (herein, roads) in
the Brazilian Amazon using artificial intelligence (AI). In this region, roads are built by …

RoadVecNet: a new approach for simultaneous road network segmentation and vectorization from aerial and google earth imagery in a complex urban set-up

A Abdollahi, B Pradhan, A Alamri - GIScience & Remote Sensing, 2021 - Taylor & Francis
In this study, we present a new automatic deep learning-based network named Road
Vectorization Network (RoadVecNet), which comprises interlinked UNet networks to …

Road extraction from a high spatial resolution remote sensing image based on richer convolutional features

Z Hong, D Ming, K Zhou, Y Guo, T Lu - IEEE Access, 2018 - ieeexplore.ieee.org
The extraction and vectorization of roads from high spatial resolution remote sensing
(HSRRS) images are of great significance to city planning and development. However …

[PDF][PDF] DEEP LEARNING APPROACH FOR ROAD EXTRACTION FROM REMOTE SENSING IMAGERY.

MAA Sheikh, T Maity, A Kole - ICTACT Journal on Soft Computing, 2023 - ictactjournals.in
Abstract In recent years, Deep Learning (DL) is proving very successful set of tools for
several image analysis, segmentation, and classification tasks. In this paper an automated …

Redes neuronales celulares, una alternativa para el análisis y modelado espacial de conectividad.

J Manuel - 2017 - centrogeo.repositorioinstitucional.mx
En los últimos años, el interés del análisis espacial se ha enfocado en la aplicación de los
sistemas de información geográfica, la percepción remota y los sistemas de navegación por …

[引用][C] 基于CNN 同心邻域极值的多车道智能交通系统图像多车牌区域的边缘检测

谢康, 杨义先, 张玲, 杜晓峰, 辛阳 - 高技术通讯, 2014

[引用][C] Research of hierarchical intrusion detection model based on discrete cellular neural networks

K Xie, Y Yang, L Zhang, W Li, Y Xin - JOURNAL OF INFORMATION …, 2013