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The babyPose dataset

Articolo
Data di Pubblicazione:
2020
Abstract:
The database here described contains data relevant to preterm infants' movement acquired in neonatal intensive care units (NICUs). The data consists of 16 depth videos recorded during the actual clinical practice. Each video consists of 1000 frames (i.e., 100s). The dataset was acquired at the NICU of the Salesi Hospital, Ancona (Italy). Each frame was annotated with the limb-joint location. Twelve joints were annotated, i.e., left and right shoul- der, elbow, wrist, hip, knee and ankle. The database is freely accessible at http: //doi.org/10.5281/zenodo.3891404. This dataset represents a unique resource for artificial intelligence researchers that want to develop algorithms to provide healthcare professionals working in NICUs with decision support. Hence, the babyPose dataset is the first annotated dataset of depth images relevant to preterm infants' movement analysis.
Tipologia CRIS:
1.1 Articolo in rivista
Keywords:
Artificial intelligence; Depth images; Neonatal intensive care units; Pose estimation; Preterm infants
Elenco autori:
Migliorelli, Lucia; Moccia, Sara; Pietrini, Rocco; Carnielli, Virgilio Paolo; Frontoni, Emanuele
Autori di Ateneo:
MOCCIA SARA
Link alla scheda completa:
https://ricerca.unich.it/handle/11564/828527
Link al Full Text:
https://ricerca.unich.it//retrieve/handle/11564/828527/426206/1-s2.0-S2352340920312221-main.pdf
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URL

https://www.sciencedirect.com/science/article/pii/S2352340920312221?via=ihub
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