Zobrazeno 1 - 10
of 83
pro vyhledávání: '"Kunlun Qi"'
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 129, Iss , Pp 103840- (2024)
With the introduction of deep learning methods, the computation required for remote sensing change detection has significantly increased, and distributed computing is applied to remote sensing change detection to improve computational efficiency. How
Externí odkaz:
https://doaj.org/article/9e0c10375eda4e0f83ac81685ab472e0
Publikováno v:
In Computers and Geosciences March 2024 185
Publikováno v:
IET Intelligent Transport Systems, Vol 15, Iss 3, Pp 396-405 (2021)
Abstract Understanding the movement of pedestrians and predicting their future trajectory can be very important in intelligent transportation systems because accurate pedestrian trajectory prediction will improve the level of autonomous driving techn
Externí odkaz:
https://doaj.org/article/1a7d98e97ed34cfd879c7135d99f1355
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 3533-3545 (2021)
Time series normalized difference vegetation index (NDVI) is the primary data for agricultural remote sensing monitoring. Due to the tradeoff between a single sensor's spatial and temporal resolutions and the impacts of cloud coverage, the time serie
Externí odkaz:
https://doaj.org/article/de15e65ec0004fa1bdcc504cf238c72f
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 7857-7868 (2021)
Remote sensing imagery typically comprises successive background contexts and complex objects. Global average pooling is a popular choice to connect the convolutional and fully connected (FC) layers for the deep convolution network. This article equi
Externí odkaz:
https://doaj.org/article/0f837d69cbd24990a2954642ef9557fd
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 13, Pp 632-641 (2020)
Most existing deep learning-based methods use feature maps extracted from convolutional neural networks (CNNs) for classification and detection of high-resolution remote sensing images (HRSIs). However, directly applying these features to classificat
Externí odkaz:
https://doaj.org/article/340f33282d69472f8b10b1c850171dd1
Publikováno v:
Remote Sensing, Vol 14, Iss 6, p 1478 (2022)
Scene classification is an active research area in the remote sensing (RS) domain. Some categories of RS scenes, such as medium residential and dense residential scenes, would contain the same type of geographical objects but have various spatial dis
Externí odkaz:
https://doaj.org/article/0da8bf8e8f074f5f89fb8e8a97d710ea
Publikováno v:
Remote Sensing, Vol 13, Iss 21, p 4475 (2021)
Ecological environment quality is a long-term continuous concept that is affected by various environmental factors. Its assessment has important implications for implementing the planning and protection of dynamic regional ecosystems. Therefore, this
Externí odkaz:
https://doaj.org/article/558369987bac4805b57a6d8dea0e43db
Publikováno v:
Remote Sensing, Vol 13, Iss 4, p 569 (2021)
Deep convolutional neural networks (DCNNs) have shown significant improvements in remote sensing image scene classification for powerful feature representations. However, because of the high variance and volume limitations of the available remote sen
Externí odkaz:
https://doaj.org/article/a03283c864dc4cfbb899a825a23db533
Publikováno v:
ISPRS Journal of Photogrammetry and Remote Sensing. 182:52-66
Change detection methods can achieve high learning ability and recognition accuracy with the introduction of deep convolutional neural networks, but due to the influence of the convolution kernel and deep feature sampling, problems such as the limite
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::37fd3647721e6bd9d9c7fc629f78a9fa
https://doi.org/10.1016/j.isprsjprs.2021.10.001
https://doi.org/10.1016/j.isprsjprs.2021.10.001