Self-supervised Learning for Endoscopic Video Analysis

Author:

Hirsch Roy,Caron Mathilde,Cohen Regev,Livne Amir,Shapiro Ron,Golany Tomer,Goldenberg Roman,Freedman Daniel,Rivlin Ehud

Publisher

Springer Nature Switzerland

Reference34 articles.

1. Antonelli, G., Rizkala, T., Iacopini, F., Hassan, C.: Current and future implications of artificial intelligence in colonoscopy. Ann. Gastroenterol. 36(2), 114–122 (2023)

2. Assran, M., et al.: Masked siamese networks for label-efficient learning. In: ECCV (2022). https://doi.org/10.1007/978-3-031-19821-2_26

3. Byrne, M.F., Shahidi, N., Rex, D.K.: Will computer-aided detection and diagnosis revolutionize colonoscopy? Gastroenterology 153(6), 1460–1464 (2017)

4. Lecture Notes in Computer Science;M Caron,2018

5. Caron, M., Misra, I., Mairal, J., Goyal, P., Bojanowski, P., Joulin, A.: Unsupervised learning of visual features by contrasting cluster assignments. In: NeurIPS (2020)

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1. Self-supervised Polyp Re-identification in Colonoscopy;Lecture Notes in Computer Science;2023

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