Laparoscopic Tool Classification in Gynaecological Images Using Convolutional Neural Network and Attention Modules : 12th IFAC Symposium on Biological and Medical Systems BMS 2024, September 11-13, 2024, Villingen-Schwenningen, Germany

Laparoscopic Tool Classification in Gynaecological Images Using Convolutional Neural Network and Attention Modules

Metadaten
Document Type:	Article (peer-reviewed)
Author:	Tamer Abdulbaki Alshirbaji ORCiD GND, Nour A. Jalal ORCiD GND, Herag Arabian ORCiD GND, Paul D. Docherty ORCiD GND, Hisham ElMoaqet, Thomas Neumuth, Knut Möller ORCiD GND
URN:	https://urn:nbn:de:bsz:fn1-opus4-112151
DOI:	https://doi.org/10.1016/j.ifacol.2024.11.068
ISSN:	2405-8963
Parent Title (English):	IFAC-PapersOnLine
Subtitle (English):	12th IFAC Symposium on Biological and Medical Systems BMS 2024, September 11-13, 2024, Villingen-Schwenningen, Germany
Language:	English
Year of Completion:	2024
Release Date:	2024/12/19
Tag:	Peer-reviewed conference Attention module; Convolutional neural network (CNN); Deep learning; Gynaecological procedures; Laparoscopic images; Surgical tool classification
Volume:	58.2024
Issue:	24
First Page:	386
Last Page:	390
Open-Access-Status:	Open Access
	Diamond
Licence (German):	Creative Commons - CC BY-NC-ND - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International