Uterine Synchronization Analysis During Pregnancy and Labor Using Graph Theory, Classification Based on Neural Network and Deep Learning - Université de technologie de Compiègne Access content directly
Journal Articles Innovation and Research in BioMedical engineering Year : 2021

Uterine Synchronization Analysis During Pregnancy and Labor Using Graph Theory, Classification Based on Neural Network and Deep Learning

Domains

Signal and Image processing Machine Learning [stat.ML]

Catherine Marque  : Connect in order to contact the contributor

https://hal.utc.fr/hal-03521626

Submitted on : Tuesday, January 11, 2022-4:48:48 PM

Last modification on : Wednesday, April 12, 2023-9:54:09 AM

No file

Dates and versions

hal-03521626 , version 1 (11-01-2022)

Identifiers

Cite

K.B. El Dine, N. Nader, M. Khalil, C. Marque. Uterine Synchronization Analysis During Pregnancy and Labor Using Graph Theory, Classification Based on Neural Network and Deep Learning. Innovation and Research in BioMedical engineering, 2021, ⟨10.1016/j.irbm.2021.09.002⟩. ⟨hal-03521626⟩

Export

BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite

Collections

CNRS UNIV-COMPIEGNE BMBI
13 View
0 Download

Altmetric

Share

Gmail Facebook X LinkedIn More