Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Heidar Rastiveis"'
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 122, Iss , Pp 103450- (2023)
Rapid assessment of urban damages after a strong earthquake is a necessary and crucial task to reduce the number of fatalities and recover socioeconomic services. In this paper, a novel deep-learning-based framework is proposed for detecting and mapp
Externí odkaz:
https://doaj.org/article/2e7d6f0970934b24b210d0018ad8a372
Autor:
Mahdiye Zaboli, Heidar Rastiveis, Benyamin Hosseiny, Danesh Shokri, Wayne A. Sarasua, Saeid Homayouni
Publikováno v:
Remote Sensing, Vol 15, Iss 9, p 2317 (2023)
The 3D semantic segmentation of a LiDAR point cloud is essential for various complex infrastructure analyses such as roadway monitoring, digital twin, or even smart city development. Different geometric and radiometric descriptors or diverse combinat
Externí odkaz:
https://doaj.org/article/5aef3f603d2c4188a951ab2e91af9368
Autor:
Young-Ha Shin, Sang-Yeop Shin, Heidar Rastiveis, Yi-Ting Cheng, Tian Zhou, Jidong Liu, Chunxi Zhao, Günder Varinlioğlu, Nicholas K. Rauh, Sorin Adam Matei, Ayman Habib
Publikováno v:
Remote Sensing, Vol 15, Iss 7, p 1876 (2023)
The utilization of remote sensing technologies for archaeology was motivated by their ability to map large areas within a short time at a reasonable cost. With recent advances in platform and sensing technologies, uncrewed aerial vehicles (UAV) equip
Externí odkaz:
https://doaj.org/article/64ab19d094f345dbb3d60dc59298b004
Publikováno v:
Remote Sensing, Vol 14, Iss 9, p 2214 (2022)
Building damage maps can be generated from either optical or Light Detection and Ranging (Lidar) datasets. In the wake of a disaster such as an earthquake, a timely and detailed map is a critical reference for disaster teams in order to plan and perf
Externí odkaz:
https://doaj.org/article/fbb30de95fcd4b0d8fbe9c9718e697b4
Publikováno v:
Remote Sensing, Vol 12, Iss 21, p 3521 (2020)
Traditional mapping and monitoring of agricultural fields are expensive, laborious, and may contain human errors. Technological advances in platforms and sensors, followed by artificial intelligence (AI) and deep learning (DL) breakthroughs in intell
Externí odkaz:
https://doaj.org/article/44466b98e812438386884353dbed1560
Autor:
Saied Pirasteh, Pejman Rashidi, Heidar Rastiveis, Shengzhi Huang, Qing Zhu, Guoxiang Liu, Yun Li, Jonathan Li, Erfan Seydipour
Publikováno v:
Remote Sensing, Vol 11, Iss 11, p 1272 (2019)
The world has experienced urban changes rapidly, and this phenomenon encourages authors to contribute to the United Nations sustainable development goals (SDGs) 2030 and geospatial information. This study presents a proposed algorithm of change detec
Externí odkaz:
https://doaj.org/article/bad24bb7ca664264bc0e398a6a46c873
Autor:
Alireza Shams, Wayne A. Sarasua, Brook T. Russell, William J. Davis, Christopher Post, Heidar Rastiveis, Afshin Famili, Leo Cassule
Publikováno v:
Transportation Research Record: Journal of the Transportation Research Board. 2677:372-384
Adequate water pavement surface drainage on highways is crucial in minimizing the potential of hydroplaning. Highway cross slope has a significant effect of draining water laterally from the pavement surface. Currently, field surveying techniques and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4b453f4512d6928a1d8d16ed78d36424
https://doi.org/10.1177/03611981221106482
https://doi.org/10.1177/03611981221106482
Autor:
Danesh Shokri, Heidar Rastiveis, Wayne A. Sarasua, Saeid Homayouni, Benyamin Hosseiny, Alireza Shams
Publikováno v:
Geographical Research.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f67b2747c33136cb4ff9967c66800096
https://doi.org/10.1111/1745-5871.12604
https://doi.org/10.1111/1745-5871.12604