Zobrazeno 1 - 10
of 237
pro vyhledávání: '"aerial remote sensing"'
Autor:
Junaid Ali Khan, Muhammad Attique Khan, Mohammed Al-Khalidi, Dina Abdulaziz AlHammadi, Areej Alasiry, Mehrez Marzougui, Yudong Zhang, Faheem Khan
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 18, Pp 337-351 (2025)
The diversity, noise, interimage interference, image distortion, and increase in the number of classes in aerial remotely sensed dataset cause exertion in the classification. The efficacy and stability of convolutional neural networks increase in ima
Externí odkaz:
https://doaj.org/article/8930b064bea04faa9e5d438dcd4adccd
Autor:
Huiying Wang, Chunping Wang, Qiang Fu, Binqiang Si, Dongdong Zhang, Renke Kou, Ying Yu, Changfeng Feng
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 15269-15287 (2024)
With the rapid advancements in deep learning technology, various deep learning-based object detection algorithms have found extensive applications in UAV-related tasks. However, motivated by the fact that current object detection algorithms for unimo
Externí odkaz:
https://doaj.org/article/2cf0880d0fb44bc5bb3c474eb76085e9
Publikováno v:
Remote Sensing, Vol 16, Iss 22, p 4194 (2024)
Semantic segmentation of vegetation in aerial remote sensing images is a critical aspect of vegetation mapping. Accurate vegetation segmentation effectively informs real-world production and construction activities. However, the presence of species h
Externí odkaz:
https://doaj.org/article/226251b1d7c8419d8154e70fd7779e54
Publikováno v:
Remote Sensing, Vol 16, Iss 15, p 2866 (2024)
The frequency of natural disasters has increased recently, posing a huge threat to human society. Rapid, accurate, authentic, and comprehensive acquisition and transmission of disaster information are crucial in emergency response. In this paper, we
Externí odkaz:
https://doaj.org/article/d1ff018e561742498df298847f3d618b
Autor:
Dimitris Kaimaris
Publikováno v:
Land, Vol 13, Iss 7, p 997 (2024)
Aerial and remote sensing archaeology are tools for identifying marks on images of archaeological remains covered by soil. In other words, they are archaeological prospection tools that fall into the category of non-destructive research methods. In t
Externí odkaz:
https://doaj.org/article/375004683c7041f38e9468550271f56e
Publikováno v:
Open Computer Science, Vol 14, Iss 1, Pp pp. 2849-2858 (2024)
Aerial photo target detection in remote sensing utilizes high-resolution aerial images, along with computer vision techniques, to identify and pinpoint specific objects. To tackle imprecise detection caused by the random arrangement of objects, a two
Externí odkaz:
https://doaj.org/article/acb984d6bd5c43e1b10f4f8382070968
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 16, Pp 8191-8203 (2023)
Detection of damaged buildings is a form of object detection and is essential for disaster emergency response efforts. In recent years, deep learning has been widely used in object detection, with successful target detection models such as Faster-Rcn
Externí odkaz:
https://doaj.org/article/81f7e16715cd467fa410ece3f1834e5e
Akademický článek
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Akademický článek
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Autor:
Shiou Li, Xianyun Fei, Peilong Chen, Zhen Wang, Yajun Gao, Kai Cheng, Huilong Wang, Yuanzhi Zhang
Publikováno v:
Remote Sensing, Vol 16, Iss 1, p 31 (2023)
The composition and structure of mountain vegetation are complex and changeable, and thus urgently require the integration of Object-Based Image Analysis (OBIA) and Deep Convolutional Neural Networks (DCNNs). However, while integration technology stu
Externí odkaz:
https://doaj.org/article/cf40cc8293c34c228eb3d88cf494d1e1