Endoscopic Detection And Segmentation Of Gastroenterological Diseases With Deep Convolutional Neural Networks. - Adrian Krenzer; Amar Hekalo; Frank Puppe (EndoCV@ISBI, 2020)

A translational pathway of deep learning methods in GastroIntestinal Endoscopy. - Sharib Ali; Mariia Dmitrieva; Noha M. Ghatwary; Sophia Bano; Gorkem Polat; Alptekin Temizel; Adrian Krenzer; Amar Hekalo; Yun Bo Guo; Bogdan J. Matuszewski; Mourad Gridach; Irina Voiculescu; et al. (CoRR, 2020)

Semi-Automated Machine Learning Video Annotation for Gastroenterologists. - Adrian Krenzer; Kevin Makowski; Amar Hekalo; Frank Puppe (MIE, 2021)

Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy. - Sharib Ali; Mariia Dmitrieva; Noha M. Ghatwary; Sophia Bano; Gorkem Polat; Alptekin Temizel; Adrian Krenzer; Amar Hekalo; Yun Bo Guo; Bogdan J. Matuszewski; Mourad Gridach; Irina Voiculescu; et al. (Medical Image Anal., 2021)

A Real-Time Polyp-Detection System with Clinical Application in Colonoscopy Using Deep Convolutional Neural Networks. - Adrian Krenzer; Michael Banck; Kevin Makowski; Amar Hekalo; Daniel Fitting; Joel Troya; Boban Sudarevic; Wolfgang G. Zoller; Alexander Hann; Frank Puppe (J. Imaging, 2023)

QBI: Quantile-based Bias Initialization for Efficient Private Data Reconstruction in Federated Learning. - Micha V. Nowak; Tim P. Bott; David Khachaturov; Frank Puppe; Adrian Krenzer; Amar Hekalo (CoRR, 2024)