Citations refer to the original publication, not to a Scieee localized version.
López Fandiño, J., Blanco Heras, D., & Argüello Pedreira, F. (2024). Using heterogeneous computing and edge computing to accelerate anomaly detection in remotely sensed multispectral images. Springer. https://doi.org/10.1007/s11227-024-05918-z
López Fandiño, Javier, et al. Using heterogeneous computing and edge computing to accelerate anomaly detection in remotely sensed multispectral images. Springer, 2024. https://doi.org/10.1007/s11227-024-05918-z.
López Fandiño, Javier, Dora Blanco Heras, and Francisco Argüello Pedreira. Using heterogeneous computing and edge computing to accelerate anomaly detection in remotely sensed multispectral images. Springer, 2024. https://doi.org/10.1007/s11227-024-05918-z.
López Fandiño, J., Blanco Heras, D. and Argüello Pedreira, F. (2024) Using heterogeneous computing and edge computing to accelerate anomaly detection in remotely sensed multispectral images. Springer. Available at: https://doi.org/10.1007/s11227-024-05918-z.
J. López Fandiño, D. Blanco Heras, and F. Argüello Pedreira, “Using heterogeneous computing and edge computing to accelerate anomaly detection in remotely sensed multispectral images,” Springer, 2024, doi: 10.1007/s11227-024-05918-z.
@misc{lopezfandino2024using,
author = {López Fandiño, Javier and Blanco Heras, Dora and Argüello Pedreira, Francisco},
title = {Using heterogeneous computing and edge computing to accelerate anomaly detection in remotely sensed multispectral images},
year = {2024},
publisher = {Springer},
doi = {10.1007/s11227-024-05918-z},
url = {https://doi.org/10.1007/s11227-024-05918-z}
}
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