Real-time patient monitoring and fall detection using pose estimation and time sequence models

Real-time patient monitoring and fall detection using pose estimation and time sequence models

Bibliographische Detailangaben
1. Verfasser: Suarez, Jessie James P. (VerfasserIn)
Weitere Verfasser: Naval, Prospero C. Jr (adviser.)
Format: Abschlussarbeit
Sprache:English
Veröffentlicht: Quezon City College of Engineering, University of the Philippines Diliman 2022.
Schlagworte:
Human activity recognition.
Artificial intelligence.
Computer vision.
Deep learning (Machine learning) .
Image processing.
Machine learning.
Neural networks (Computer science)
Online Zugang:Abstract