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Filters: 1 is biblio_year:2022 and Author is Håvard D. Johansen [Reset Search]
Filters: 1 is biblio_year:2022 and Author is Håvard D. Johansen [Reset Search]
 "A comprehensive analysis of classification methods in gastrointestinal endoscopy imaging." Medical Image Analysis 70 (2021): 102007. 2.pdf (3.22 MB)
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 2.pdf (3.22 MB) "A Comprehensive Study on Colorectal Polyp Segmentation with ResUNet++, Conditional Random Field and Test-Time Augmentation." IEEE Journal of Biomedical and Health Informatics 25, no. 6 (2021): 2029-2040. 09314114.pdf (6.16 MB)
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 09314114.pdf (6.16 MB) DDANet: Dual Decoder Attention Network for Automatic Polyp Segmentation In 25th International Conference on Pattern Recognition.  Springer, 2021. endotect_segmentation_debesh.pdf (4.12 MB)
 endotect_segmentation_debesh.pdf (4.12 MB)
 endotect_segmentation_debesh.pdf (4.12 MB)
 endotect_segmentation_debesh.pdf (4.12 MB) DeepSynthBody: the beginning of the end for data deficiency in medicine In The International Conference on Applied Artificial Intelligence (ICAPAI). IEEE, 2021.
 Kvasir-Instrument: Diagnostic and therapeutic tool segmentation dataset in gastrointestinal endoscopy In 27th International Conference on Multimedia Modeling. Vol. LNCS, volume 12573. Springer, 2021. mmm.pdf (648.64 KB)
 mmm.pdf (648.64 KB)
 mmm.pdf (648.64 KB)
 mmm.pdf (648.64 KB) Kvasir-SEG: A Segmented Polyp Dataset In International Conference on Multimedia Modeling. Daejeon, Korea: Springer, 2020. mmm_2020_kvasir_seg_debesh.pdf (4.04 MB)
 mmm_2020_kvasir_seg_debesh.pdf (4.04 MB)
 mmm_2020_kvasir_seg_debesh.pdf (4.04 MB)
 mmm_2020_kvasir_seg_debesh.pdf (4.04 MB) LightLayers: Parameter Efficient Dense and Convolutional Layers for Image Classification In The Joint International Conference PDCAT-PAAP 2020.  Springer, 2020. pdcat_paap_springer_debesh.pdf (288.65 KB)
 pdcat_paap_springer_debesh.pdf (288.65 KB)
 pdcat_paap_springer_debesh.pdf (288.65 KB)
 pdcat_paap_springer_debesh.pdf (288.65 KB) Medico Multimedia Task at MediaEval 2020: Automatic Polyp Segmentation In Medico MediaEval 2020. CEUR, 2020. 2020_automatic_polyp_segmentation_challenge_debesh.pdf (1.49 MB)
 2020_automatic_polyp_segmentation_challenge_debesh.pdf (1.49 MB)
 2020_automatic_polyp_segmentation_challenge_debesh.pdf (1.49 MB)
 2020_automatic_polyp_segmentation_challenge_debesh.pdf (1.49 MB) The Medico-Task 2018: Disease Detection in the Gastrointestinal Tract using Global Features and Deep Learning In MediaEval 2018. Nice, France: MediaEval, 2018. mediaeval_team_dv_10.pdf (374.73 KB)
 mediaeval_team_dv_10.pdf (374.73 KB)
 mediaeval_team_dv_10.pdf (374.73 KB)
 mediaeval_team_dv_10.pdf (374.73 KB)