Proceedings of the EndoCV 2020 - 2nd International Workshop and Challenge on Computer Vision in Endoscopy : in conjunction with the 17th International Symposium on Biomedical Imaging (ISBI2020), Iowa, USA, April 3, 2020 (English)
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2020
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Title:Proceedings of the EndoCV 2020 - 2nd International Workshop and Challenge on Computer Vision in Endoscopy : in conjunction with the 17th International Symposium on Biomedical Imaging (ISBI2020), Iowa, USA, April 3, 2020
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Additional title:EndoCV 2020 - 2nd International Workshop and Challenge on Computer Vision in Endoscopy
EndoCV2020: Computer Vision in Endoscopy -
Contributors:Ali, Sharib ( editor ) / Daul, Christian ( editor ) / Rittscher, Jens ( editor ) / Stoyanov, Danail ( editor ) / Grisan, Enrico ( editor ) / International Workshop and Challenge on Computer Vision in Endoscopy ( author )
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Conference:International Workshop and Challenge on Computer Vision in Endoscopy ; 2020 ; Iowa City, Iowa
Endoscopy Computer Vision Challenge and Workshop ; 2020 ; Iowa City, Iowa
Workshop on Computer Vision in Endoscopy ; 2020 ; Iowa City, Iowa
EndoCV ; 2020 ; Iowa City, Iowa
Endoscopy Artefact Detection and Segmentation (EAD) ; 2020 ; Iowa City, Iowa
Endoscopy Disease Detection and Segmentation (EDD) ; 2020 ; Iowa City, Iowa
International Symposium on Biomedical Imaging ; 17 ; 2020 ; Iowa City, Iowa
IEEE ISBI ; 17 ; 2020 ; Iowa City, Iowa
ISBI ; 17 ; 2020 ; Iowa City, Iowa -
Published in:CEUR workshop proceedings ; vol-2595
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Publisher:
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Place of publication:[Aachen, Germany]
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Publication date:2020
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Size:1 Online-Ressource
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Remarks:Illustrationen
Literaturangaben
"This year EndoCV2020 is introduced with two sub-challenge themes this year: Sub-challenge I: Endoscopy Artefact Detection and Segmentation (EAD2020); Sub-challenge II: Endoscopy Disease Detection and Segmentation (EDD2020)" - EndoCV2020-Homepage
Digital preservation by Technische Informationsbibliothek (TIB) / Leibniz-Informationszentrum Technik und Naturwissenschaften und Universitätsbibliothek -
Type of media:Conference Proceedings
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Type of material:Electronic Resource
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Language:English
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Licence:
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Source:
The tables of contents are generated automatically and are based on the data records of the individual contributions available in the index of the TIB portal. The display of the Tables of Contents may therefore be incomplete.
- 1
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Endoscopic Artefact Detection with Ensemble of Deep Neural Networks and False Positive EliminationPolat, Gorkem / Sen, Deniz / Inci, Alperen / Temizel, Alptekin et al. | 2020
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A U-Net++ With Pre-Trained EfficientNet Backbone for Segmentation of Diseases and Artifacts in Endoscopy Images and VideosHuynh, Le Duy / Boutry, Nicolas et al. | 2020
- 3
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Deep Encoder-decoder Networks for Artefacts Segmentation in Endoscopy ImagesGuo, Yun Bo / Zheng, Qingshuo / Matuszewski, Bogdan J. et al. | 2020
- 4
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Multi-plateau Ensemble For Endoscopic Artefact Segmentation And DetectionJadhav, Suyog / Bamba, Udbhav / Chavan, Arnav / Tiwari, Rishabh / Raj, Aryan et al. | 2020
- 5
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OXENDONET: A Dilated Convolutional Neural Networks For Endoscopic Artefact SegmentationGridach, Mourad / Voiculescu, Irina et al. | 2020
- 6
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A Submission Note on EAD 2020: Deep Learning based Approach for Detecting Artefacts in EndoscopyY, Vishnusai / Prakash, Prithvi / Shivashankar, Nithin et al. | 2020
- 7
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Endoscopy Artefact Detection and Segmentation using Deep Convolutional Neural NetworkChen, Haijian / Lian, Chenyu / Wang, Liansheng et al. | 2020
- 8
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Endoscopic Artefact Detection using Cascade R-CNN based ModelYu, Zhimiao / Guo, Yuanfan et al. | 2020
- 9
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Artefact Detection and Segmentation Using Cascade R-CNN and U-NetHung, Hoang Manh / Thinh, Phan Tran Dac / Yang, Hyung-Jeong / Kim, Soo-Hyung / Lee, Guee-Sang et al. | 2020
- 10
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Exploring Deep Learning Based Approaches for Endoscopic Artefact Detection and SegmentationSubramanian, Anand / Srivatsan, Koushik et al. | 2020
- 11
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Endoscopic Detection And Segmentation Of Gastroenterological Diseases With Deep Convolutional Neural NetworksKrenzer, Adrian / Hekalo, Amar / Puppe, Frank et al. | 2020
- 12
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Detection and Segmentation of Endoscopic Artefacts and Diseases Using Deep ArchitecturesNguyen, Nhan T. / Tran, Dat Q. / Nguyen, Dung B. et al. | 2020
- 13
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Transfer Learning For Endoscopy Disease Detection & Segmentation With Mask-RCNN Benchmark ArchitectureRezvy, Shahadate / Zebin, Tahmina / Braden, Barbara / Pang, Wei / Taylor, Stephen / Gao, Xiaohong W et al. | 2020
- 14
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Centernet-based Detection Model And U-net-based Multi-class Segmentation Model For Gastrointestinal DiseasesChoi, Yoon Ho / Lee, Yeong Chan / Hong, Sanghoon / Kim, Junyoung / Won, Hong-Hee / Kim, Taejun et al. | 2020
- 15
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Endoscopic Artefact Detection in MMDetectionHu, Hongyu / Guo, Yuanfan et al. | 2020
- 16
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Artefact Detection and Segmentation based on a Deep Learning systemGao, Xiaohong (Sharon) / Braden, Barbara et al. | 2020
- 17
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Semantic Segmentation, Detection AND Localisation of Mucosal Lesions from Gastrointestinal Endoscopic Images Using SUMNETBalasubramanian, Velmurugan / Kumar, Rajiv / Kamireddi, Sarasa Jyothsna / Sathish, Rachana / Sheet, Debdoot et al. | 2020
- 18
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Deep Learning based Approach for Detecting Diseases in EndoscopyY, Vishnusai / Prakash, Prithvi / Shivashankar, Nithin et al. | 2020