Consistency Loss for Improved Colonoscopy Landmark Detection with Vision Transformers

Author:

Tamhane Aniruddha,Dobkin Daniel,Shtalrid Ore,Bouhnik Moshe,Posner Erez,Mida Tse’ela

Publisher

Springer Nature Switzerland

Reference33 articles.

1. Advances in Intelligent Systems and Computing;S Adewole,2021

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3. Cao, Y., Liu, D., Tavanapong, W., Wong, J., Oh, J., De Groen, P.C.: Automatic classification of images with appendiceal orifice in colonoscopy videos. In: 2006 International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 2349–2352. IEEE (2006)

4. Chawla, N.V., Bowyer, K.W., Hall, L.O., Kegelmeyer, W.P.: SMOTE: synthetic minority over-sampling technique. J. Artif. Intell. Res. 16, 321–357 (2002)

5. Che, K., et al.: Deep learning-based biological anatomical landmark detection in colonoscopy videos. arXiv preprint arXiv:2108.02948 (2021)

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