Surgical Tool Classification in Laparoscopic Videos Using Convolutional Neural Network
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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Online-Ressource
- Language
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Englisch
- Bibliographic citation
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In: Current Directions in Biomedical Engineering 4.2018, 1, S. 407-410
- Event
-
Veröffentlichung
- (where)
-
Furtwangen
- (who)
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Hochschule Furtwangen
- (when)
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2018
- DOI
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10.1515/cdbme-2018-0097
- URN
-
urn:nbn:de:bsz:fn1-opus4-47988
- Rights
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
25.03.2025, 1:43 PM CET
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Abdulbaki Alshirbaji, Tamer
- Jalal, Nour Aldeen
- Möller, Knut
- Hochschule Furtwangen
Time of origin
- 2018
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Robustness of Convolutional Neural Networks for Surgical Tool Classification in Laparoscopic Videos from Multiple Sources and of Multiple Types: A Systematic Evaluation
A convolutional neural network with a two-stage LSTM model for tool presence detection in laparoscopic videos
Evaluating Convolutional Neural Network and Hidden Markov Model for Recognising Surgical Phases in Sigmoid Resection
P-CSEM: an attention module for improved laparoscopic surgical tool detection
Fusing CNN features to improve generalisability for surgical tool classification
Spatial-temporal Modelling for Surgical Tool Classification in Cholecystectomy Videos
The Image flip effect on a CNN model classification
Features for detecting smoke in laparoscopic videos
Classifying smoke in laparoscopic videos using SVM
Assessing Generalisation Capabilities of CNN Models for Surgical Tool Classification
Predicting Surgical Phases using CNN-NARX Neural Network