Zobrazeno 1 - 10
of 2 214
pro vyhledávání: '"Remote sensing (RS)"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-20 (2024)
Abstract Understanding land use and damage in open-pit coal mining areas is crucial for effective scientific oversight and management. Current recognition methods exhibit limitations: traditional approaches depend on manually designed features, which
Externí odkaz:
https://doaj.org/article/9f45d4588dab44c3bac23e6c41609178
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 18, Pp 1085-1097 (2025)
The joint classification of multisource remote sensing data has shown significant potential in the precise interpretation of land cover. Existing methods mainly employ a dual-stream architecture to independently extract features, subsequently merging
Externí odkaz:
https://doaj.org/article/92ffeee43b2044c4996531cebbbe9abc
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 18, Pp 321-336 (2025)
Self-supervised learning guided by masked image modeling, such as masked autoencoder (MAE), has attracted wide attention for pretraining vision transformers in remote sensing. However, MAE tends to excessively focus on pixel details, limiting the mod
Externí odkaz:
https://doaj.org/article/ad141a7704a940acb0a37173d5a8ed62
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
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 18, Pp 160-175 (2025)
Remote sensing change detection (CD) is a crucial task for observing and analyzing dynamic land cover alterations. Many CD methods based on deep learning demonstrate strong performance, but their effectiveness is influenced by the choice of encoder a
Externí odkaz:
https://doaj.org/article/289004e7f1e449b48252ea29bc73debc
Autor:
Zhipeng Cao, Liangcun Jiang, Peng Yue, Jianya Gong, Xiangyun Hu, Shuaiqi Liu, Haofeng Tan, Chang Liu, Boyi Shangguan, Dayu Yu
Publikováno v:
Geo-spatial Information Science, Vol 27, Iss 5, Pp 1489-1508 (2024)
Artificial Intelligence (AI) Machine Learning (ML) technologies, particularly Deep Learning (DL), have demonstrated significant potential in the interpretation of Remote Sensing (RS) imagery, covering tasks such as scene classification, object detect
Externí odkaz:
https://doaj.org/article/35b755753428416f8762e33772c09a68
Publikováno v:
Frontiers in Plant Science, Vol 15 (2024)
Controlling crop diseases and pests is essential for intelligent agriculture (IA) due to the significant reduction in crop yield and quality caused by these problems. In recent years, the remote sensing (RS) areas has been prevailed over by unmanned
Externí odkaz:
https://doaj.org/article/afc62b0c8f924deda02fa80951ce3dbe
Hybrid deep learning and remote sensing for the delineation of artificial groundwater recharge zones
Autor:
Rami Al-Ruzouq, Abdallah Shanableh, Ratiranjan Jena, Sunanda Mukherjee, Mohamad Ali Khalil, Mohamed Barakat A. Gibril, Biswajeet Pradhan, Nezar Atalla Hammouri
Publikováno v:
Egyptian Journal of Remote Sensing and Space Sciences, Vol 27, Iss 2, Pp 178-191 (2024)
The increase in water demand and the scarcity of fresh water in arid regions have contributed to the depletion of groundwater. Artificial Groundwater Recharge (AGR) is an advanced strategy that contributes to combating water shortage issues. Limited
Externí odkaz:
https://doaj.org/article/1b79a1d08e20464a9bbcc6c1d85e045c
Autor:
Qing Zhao, Antonio Pepe, Virginia Zamparelli, Pietro Mastro, Francesco Falabella, Saygin Abdikan, Caglar Bayik, Fusun Balik Sanli, Mustafa Ustuner, Nevin Betul Avşar, Jingjing Wang, Peng Chen, Zhengjie Li, Adam T. Devlin, Fabiana Calò
Publikováno v:
Geo-spatial Information Science, Vol 27, Iss 3, Pp 836-853 (2024)
Remote sensing (RS) technologies are extensively exploited by scientists and a vast audience of local authorities, urban managers, and city planners. Coastal regions, geohazard-prone areas, and highly populated cities represent natural laboratories t
Externí odkaz:
https://doaj.org/article/e5ce94392bc6412ebb2cc19b58c4027f
Publikováno v:
Baghdad Science Journal, Vol 21, Iss 7 (2024)
Reliable and accurate crop maps are required for food security from regional to global scale. The increased availability of satellite imagery leads to a “Big Data” problem while producing crop maps. Now, cloud-based platforms have gained a lot of
Externí odkaz:
https://doaj.org/article/8e5bcb88527244989e176d2351ae0f11