Enhanced Recovery After Surgery Protocol in Minimally Invasive Lumbar Fusion Surgery Reduces Length of Hospital Stay and Inpatient Narcotic Use

Autor: Isabelle C. Band, Altan O. Yenicay, Tina D. Montemurno, Jenny S. Chan, Alfred T. Ogden

Publikováno v: World Neurosurgery: X, Vol 14, Iss , Pp 100120- (2022)

Background: The application of enhanced recovery after surgery (ERAS) has the potential to improve outcomes, hasten patient recovery, and reduce costs. ERAS has been applied to spine surgery for several years, but data are limited around the impact o

Externí odkaz: https://doaj.org/article/09e46a0f852a462d93717a2690dee12a

ADAPTATION OF DEEPLAB V3+ FOR DAMAGE DETECTION ON PORT INFRASTRUCTURE IMAGERY

Autor: Scherff, M., Hake, F., Alkhatib, H., Altan, O., Sunar, F., Klein, D.

Publikováno v: International Symposium on Remote Sensing of Environment (ISRSE-39) “From Human needs to SDGs”
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (ISPRS Archives) ; XLVIII-M-1-2023
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (ISPRS Archives)

Regular inspection and maintenance of infrastructure facilities are crucial to ensure their functionality and safety for users. However, current inspection methods are labor-intensive and can vary depending on the inspector. To improve this process,

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9deb4e1b7906b5ab7a3915d91e055f33
https://isprs-archives.copernicus.org/articles/XLVIII-M-1-2023/301/2023/

A Debiasing Variational Autoencoder for Deforestation Mapping

Autor: Ortega Adarme, M.X., Soto Vega, P.J., Costa, G.A.O.P., Feitosa, R.Q., Heipke, C., Altan, O., Sunar, F., Klein, D.

Publikováno v: International Symposium on Remote Sensing of Environment (ISRSE-39) “From Human needs to SDGs”
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (ISPRS Archives) ; XLVIII-M-1-2023
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (ISPRS Archives)

Deep Learning (DL) algorithms provide numerous benefits in different applications, and they usually yield successful results in scenarios with enough labeled training data and similar class proportions. However, the labeling procedure is a cost and t

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::15dda2668c628be3a6f49ff809af3b86

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DYNAMIC TIME WARPING FOR CROPS MAPPING

Autor: Belgiu, M., Zhou, Y., Marshall, M., Stein, A., Paparoditis, N., Mallet, C., Lafarge, F., Jiang, J., Shaker, A., Zhang, H., Liang, X., Osmanoglu, B., Soergel, U., Honkavaara, E., Scaioni, M., Zhang, J., Peled, A., Wu, L., Li, R., Yoshimura, M., Di, K., Altan, O., Abdulmuttalib, H.M., Faruque, F.S.

Publikováno v: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLIII-B3-2020, Pp 947-951 (2020)
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences: XXIV ISPRS Congress, XLIII-B3-2020, 947-951

Dynamic Time Warping (DTW) has been successfully used for crops mapping due to its capability to achieve good classification results when a reduced number of training samples and irregular satellite image time series is available. Despite its recogni

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5f1dc53722ab41307f339ea62b7bacf8
https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B3-2020/947/2020/isprs-archives-XLIII-B3-2020-947-2020.pdf