Results 61 to 70 of about 2,732,569 (203)

SWCARE: Switchable learning and connectivity-aware refinement method for multi-city and diverse-scenario road mapping using remote sensing images

International Journal of Applied Earth Observations and Geoinformation
Accurate and efficient mapping of road networks is crucial for evaluating urban development, transportation accessibility, and environmental impact.
Lixian Zhang, Shuai Yuan, Runmin Dong, Juepeng Zheng, Bin Gan, Dengmao Fang, Yang Liu, Haohuan Fu   +7 more
doaj   +1 more source

BrightEarth Roads: Towards Fully Automatic Road Network Extraction from Satellite Imagery

IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium
The modern road network topology comprises intricately designed structures that introduce complexity when automatically reconstructing road networks. While open resources like OpenStreetMap (OSM) offer road networks with well-defined topology, they may not always be up to date worldwide.
Duan, Liuyun, Mapurisa, Willard, Leras, Maxime, Lotter, Leigh, Tarabalka, Yuliya   +4 more
openaire   +3 more sources

Feature Fusion Based Road Extraction for HJ-1-C SAR Image

Leida xuebao, 2014
Road network extraction in SAR images is one of the key tasks of military and civilian technologies. To solve the issues of road extraction of HJ-1-C SAR images, a road extraction algorithm is proposed based on the integration of ratio and directional ...
Lu Ping-ping, Du Kang-ning, Yu Wei-dong, Wang Yu, Deng Yun-kai   +4 more
doaj   +1 more source

Road Extraction using Connected Component Techniques

International Journal of Engineering & Technology, 2018
Extraction of Roads, Rivers and other map objects is an important step in many military and civilian applications. In this process the information is extracted which possess high efficiency and accuracy and is fed into GIS (Geographical Information System). In this paper, we have explored different algorithms with better efficiency and accuracy.
J. D. Dorathi Jayaseeli, D. Malathi, Sarvesh Karandikar, Aditi Singh, Gopika S   +4 more
openaire   +2 more sources

Scan Line Based Road Marking Extraction from Mobile LiDAR Point Clouds

Sensors, 2016
Mobile Mapping Technology (MMT) is one of the most important 3D spatial data acquisition technologies. The state-of-the-art mobile mapping systems, equipped with laser scanners and named Mobile LiDAR Scanning (MLS) systems, have been widely used in a ...
Li Yan, Hua Liu, Junxiang Tan, Zan Li, Hong Xie, Changjun Chen   +5 more
doaj   +1 more source

Road Extraction From a High Spatial Resolution Remote Sensing Image Based on Richer Convolutional Features

IEEE Access, 2018
The extraction and vectorization of roads from high spatial resolution remote sensing (HSRRS) images are of great significance to city planning and development.
Zhaoli Hong, Dongping Ming, Keqi Zhou, Ya Guo, Tingting Lu   +4 more
doaj   +1 more source

Characterisation of flavourous sesame oil obtained from microwaved sesame seed by subcritical propane extraction

Food Chemistry: X
This study developed a novel and green method to produce fragrant sesame oil using microwaves and subcritical extraction (SBE). Sesame seeds were microwaved at 540 W for 0–9 min before subcritical propane extraction at 40 °C and 0.5 MPa.
Fan Zhang, Xue-de Wang, Ke Li, Wen-ting Yin, Hua-min Liu, Xin-liang Zhu, Peng Hu   +6 more
doaj   +1 more source

Road Extraction by Using Atrous Spatial Pyramid Pooling Integrated Encoder-Decoder Network and Structural Similarity Loss

Remote Sensing, 2019
The technology used for road extraction from remote sensing images plays an important role in urban planning, traffic management, navigation, and other geographic applications.
Hao He, Dongfang Yang, Shicheng Wang, Shuyang Wang, Yongfei Li   +4 more
doaj   +1 more source

RIRNet: A Direction-Guided Post-Processing Network for Road Information Reasoning

Remote Sensing
Road extraction from high-resolution remote sensing images (HRSIs) is one of the tasks in image analysis. Deep convolutional neural networks have become the primary method for road extraction due to their powerful feature representation capability ...
Guoyuan Zhou, Changxian He, Hao Wang, Qiuchang Xie, Qiong Chen, Liang Hong, Jie Chen   +6 more
doaj   +1 more source

JointNet: A Common Neural Network for Road and Building Extraction

Remote Sensing, 2019
Automatic extraction of ground objects is fundamental for many applications of remote sensing. It is valuable to extract different kinds of ground objects effectively by using a general method.
Zhengxin Zhang, Yunhong Wang
doaj   +1 more source