Improving Masked Autoencoders by Learning Where to Mask

no code implementations • 12 Mar 2023 • Haijian Chen, Wendong Zhang, Yunbo Wang, Xiaokang Yang

Masked image modeling is a promising self-supervised learning method for visual data.

Image Reconstruction Self-Supervised Learning

Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy

no code implementations • 12 Oct 2020 • Sharib Ali, Mariia Dmitrieva, Noha Ghatwary, Sophia Bano, Gorkem Polat, Alptekin Temizel, Adrian Krenzer, Amar Hekalo, Yun Bo Guo, Bogdan Matuszewski, Mourad Gridach, Irina Voiculescu, Vishnusai Yoganand, Arnav Chavan, Aryan Raj, Nhan T. Nguyen, Dat Q. Tran, Le Duy Huynh, Nicolas Boutry, Shahadate Rezvy, Haijian Chen, Yoon Ho Choi, Anand Subramanian, Velmurugan Balasubramanian, Xiaohong W. Gao, Hongyu Hu, Yusheng Liao, Danail Stoyanov, Christian Daul, Stefano Realdon, Renato Cannizzaro, Dominique Lamarque, Terry Tran-Nguyen, Adam Bailey, Barbara Braden, James East, Jens Rittscher

The Endoscopy Computer Vision Challenge (EndoCV) is a crowd-sourcing initiative to address eminent problems in developing reliable computer aided detection and diagnosis endoscopy systems and suggest a pathway for clinical translation of technologies.

Data Augmentation