Laparoscopic Tool Classification in Gynaecological Images Using Convolutional Neural Network and Attention Modules
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| Author: | Tamer Abdulbaki AlshirbajiORCiDGND, Nour A. JalalORCiDGND, Herag ArabianORCiDGND, Paul D. DochertyORCiDGND, Hisham ElMoaqet, Thomas Neumuth, Knut MöllerORCiDGND |
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| 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 |
| Document Type: | Article (peer-reviewed) |
| 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 |
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| Licence (German): |  Creative Commons - CC BY-NC-ND - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International |