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Dense Depth Estimation in Monocular Endoscopy With Self-Supervised Learning Methods.

, , , , , , and . IEEE Trans. Med. Imaging, 39 (5): 1438-1447 (2020)

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When in Doubt: Improving Classification Performance with Alternating Normalization., , , , and . EMNLP (Findings), page 1716-1723. Association for Computational Linguistics, (2021)Intentonomy: A Dataset and Study Towards Human Intent Understanding., , , , , and . CVPR, page 12986-12996. Computer Vision Foundation / IEEE, (2021)S3D: Stacking Segmental P3D for Action Quality Assessment., , , , and . ICIP, page 928-932. IEEE, (2018)Feature Classification for Tracking Articulated Surgical Tools., , and . MICCAI (2), volume 7511 of Lecture Notes in Computer Science, page 592-600. Springer, (2012)A Generative Adversarial Neural Network for Beamforming Ultrasound Images Invited Presentation., , , and . CISS, page 1-6. IEEE, (2019)Self-supervised Learning for Dense Depth Estimation in Monocular Endoscopy., , , , , , and . OR 2.0/CARE/CLIP/ISIC@MICCAI, volume 11041 of Lecture Notes in Computer Science, page 128-138. Springer, (2018)Endoscopic-CT: learning-based photometric reconstruction for endoscopic sinus surgery., , , , , and . Medical Imaging: Image Processing, volume 9784 of SPIE Proceedings, page 978418. SPIE, (2016)Learning features on robotic surgical tools., , and . CVPR Workshops, page 38-43. IEEE Computer Society, (2012)Simultaneous segmentation and correspondence improvement using statistical modes., , , , , and . Medical Imaging: Image Processing, volume 10133 of SPIE Proceedings, page 101331B. SPIE, (2017)Photoacoustic Source Detection and Reflection Artifact Removal Enabled by Deep Learning., , and . IEEE Trans. Med. Imaging, 37 (6): 1464-1477 (2018)