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A self-learning teacher-student framework for gastrointestinal image classification.

H. Gjestang, S. Hicks, V. Thambawita, P. Halvorsen, and M. Riegler. CBMS, page 539-544. IEEE, (2021)

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Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challenge.S. Ali, N. Ghatwary, D. Jha, E. Isik-Polat, G. Polat, C. Yang, W. Li, A. Galdran, M. Ballester, V. Thambawita and 22 other author(s). CoRR, (2022)VISEM-Tracking: Human Spermatozoa Tracking Dataset.V. Thambawita, S. Hicks, A. Storås, T. Nguyen, J. Andersen, O. Witczak, T. Haugen, H. Hammer, P. Halvorsen, and M. Riegler. CoRR, (2022)Using 3D Convolutional Neural Networks for Real-time Detection of Soccer Events.O. Rongved, S. Hicks, V. Thambawita, H. Stensland, E. Zouganeli, D. Johansen, C. Midoglu, M. Riegler, and P. Halvorsen. Int. J. Semantic Comput., 15 (2): 161-187 (2021)DivergentNets:Medical Image Segmentation by Network Ensemble.V. Thambawita, S. Hicks, P. Halvorsen, and M. Riegler. EndoCV@ISBI, volume 2886 of CEUR Workshop Proceedings, page 27-38. CEUR-WS.org, (2021)Pyramidal Segmentation of Medical Images using Adversarial Training.E. Naess, V. Thambawita, S. Hicks, M. Riegler, and P. Halvorsen. ICDAR@ICMR, page 33-38. ACM, (2021)Overview of ImageCLEFmedical 2023 - Medical Visual Question Answering for Gastrointestinal Tract.S. Hicks, A. Storås, P. Halvorsen, T. de Lange, M. Riegler, and V. Thambawita. CLEF (Working Notes), volume 3497 of CEUR Workshop Proceedings, page 1316-1327. CEUR-WS.org, (2023)Vid2Pix - A Framework for Generating High-Quality Synthetic Videos.O. Nedrejord, V. Thambawita, S. Hicks, P. Halvorsen, and M. Riegler. ISM, page 25-26. IEEE, (2020)Automated Clipping of Soccer Events using Machine Learning.J. Valand, H. Kadragic, S. Hicks, V. Thambawita, C. Midoglu, T. Kupka, D. Johansen, M. Riegler, and P. Halvorsen. ISM, page 210-214. IEEE, (2021)Advancing Multimedia Retrieval in Medical, Social Media and Content Recommendation Applications with ImageCLEF 2024.B. Ionescu, H. Müller, A. Dragulinescu, A. Idrissi-Yaghir, A. Radzhabov, A. de Herrera, A. Andrei, A. Stan, A. Storås, A. Abacha and 28 other author(s). ECIR (6), volume 14613 of Lecture Notes in Computer Science, page 44-52. Springer, (2024)GridHTM: Grid-Based Hierarchical Temporal Memory for Anomaly Detection in Videos.V. Monakhov, V. Thambawita, P. Halvorsen, and M. Riegler. Sensors, 23 (4): 2087 (February 2023)

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A self-learning teacher-student framework for gastrointestinal image classification.

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copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML A self-learning teacher-student framework for gastrointestinal image classification.

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A self-learning teacher-student framework for gastrointestinal image classification.