Learn the new, keep the old: Extending pretrained models with new
anatomy and images

Learn the new, keep the old: Extending pretrained models with new anatomy and images

1 June 2018

Philipp Fürnstahl

Papers citing "Learn the new, keep the old: Extending pretrained models with new anatomy and images"

11 / 11 papers shown

Title
FALCON: Fairness Learning via Contrastive Attention Approach to Continual Semantic Scene Understanding Thanh-Dat Truong Utsav Prabhu Bhiksha Raj Jackson Cothren Khoa Luu CLL 40 3 0 27 Nov 2023
CONDA: Continual Unsupervised Domain Adaptation Learning in Visual Perception for Self-Driving Cars Thanh-Dat Truong Pierce Helton A. Moustafa J. Cothren Khoa Luu CLL 53 7 0 01 Dec 2022
Domain-incremental Cardiac Image Segmentation with Style-oriented Replay and Domain-sensitive Feature Whitening Kang Li Lequan Yu Pheng-Ann Heng CLL 24 22 0 09 Nov 2022
Modeling the Background for Incremental and Weakly-Supervised Semantic Segmentation Fabio Cermelli Massimiliano Mancini Samuel Rota Buló Elisa Ricci Barbara Caputo CLL 31 8 0 31 Jan 2022
Continual Active Learning for Efficient Adaptation of Machine Learning Models to Changing Image Acquisition Matthias Perkonigg J. Hofmanninger Georg Langs MedIm OOD 38 16 0 07 Jun 2021
Replay in Deep Learning: Current Approaches and Missing Biological Elements Tyler L. Hayes G. Krishnan M. Bazhenov H. Siegelmann T. Sejnowski Christopher Kanan CLL 38 130 0 01 Apr 2021
Self-Training for Class-Incremental Semantic Segmentation Lu Yu Xialei Liu Joost van de Weijer CLL SSL 28 54 0 06 Dec 2020
Modeling the Background for Incremental Learning in Semantic Segmentation Fabio Cermelli Massimiliano Mancini Samuel Rota Buló Elisa Ricci Barbara Caputo CLL VLM 24 277 0 03 Feb 2020
Active Learning for Segmentation Based on Bayesian Sample Queries Firat Özdemir Z. Peng Philipp Fürnstahl C. Tanner O. Goksel 33 22 0 22 Dec 2019
Active Learning for Segmentation by Optimizing Content Information for Maximal Entropy Firat Özdemir Z. Peng C. Tanner Philipp Fürnstahl O. Goksel 20 28 0 18 Jul 2018
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,145 0 06 Jun 2015