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2020 – today
- 2024
[i15]Kerem Cekmeceli, Meva Himmetoglu, Guney I. Tombak, Anna Susmelj, Ertunc Erdil, Ender Konukoglu:
Do Vision Foundation Models Enhance Domain Generalization in Medical Image Segmentation? CoRR abs/2409.07960 (2024)- 2023
- [j10]Krishna Chaitanya
, Ertunc Erdil, Neerav Karani, Ender Konukoglu:
Local contrastive loss with pseudo-label based self-training for semi-supervised medical image segmentation. Medical Image Anal. 87: 102792 (2023) - [c23]Gustav Bredell, Kyriakos Flouris, Krishna Chaitanya, Ertunc Erdil, Ender Konukoglu:
Explicitly Minimizing the Blur Error of Variational Autoencoders. ICLR 2023 - [c22]Sara Sangalli, Ertunc Erdil, Ender Konukoglu:
Expert load matters: operating networks at high accuracy and low manual effort. NeurIPS 2023 - [c21]Gustav Bredell, Ertunc Erdil, Bruno Weber, Ender Konukoglu:
Wiener Guided DIP for Unsupervised Blind Image Deconvolution. WACV 2023: 3046-3055 - [i14]Gustav Bredell, Kyriakos Flouris, Krishna Chaitanya, Ertunc Erdil, Ender Konukoglu:
Explicitly Minimizing the Blur Error of Variational Autoencoders. CoRR abs/2304.05939 (2023) - [i13]Sara Sangalli, Ertunc Erdil, Ender Konukoglu:
Expert load matters: operating networks at high accuracy and low manual effort. CoRR abs/2308.05035 (2023) - 2022
- [i12]Neerav Karani, Georg Brunner, Ertunc Erdil, Simin Fei, Kerem Can Tezcan, Krishna Chaitanya, Ender Konukoglu:
A Field of Experts Prior for Adapting Neural Networks at Test Time. CoRR abs/2202.05271 (2022) - 2021
- [j9]Neerav Karani, Ertunc Erdil, Krishna Chaitanya, Ender Konukoglu:
Test-time adaptable neural networks for robust medical image segmentation. Medical Image Anal. 68: 101907 (2021) - [j8]Krishna Chaitanya, Neerav Karani, Christian F. Baumgartner, Ertunc Erdil, Anton S. Becker, Olivio Donati, Ender Konukoglu:
Semi-supervised task-driven data augmentation for medical image segmentation. Medical Image Anal. 68: 101934 (2021) - [c20]Ertunc Erdil, Krishna Chaitanya, Neerav Karani, Ender Konukoglu:
Task-Agnostic Out-of-Distribution Detection Using Kernel Density Estimation. UNSURE/PIPPI@MICCAI 2021: 91-101 - [c19]Sara Sangalli, Ertunc Erdil, Andreas M. Hötker, Olivio Donati, Ender Konukoglu:
Constrained Optimization to Train Neural Networks on Critical and Under-Represented Classes. NeurIPS 2021: 25400-25411 - [i11]Sara Sangalli, Ertunc Erdil, Andreas M. Hötker, Olivio Donati, Ender Konukoglu:
Constrained Optimization for Training Deep Neural Networks Under Class Imbalance. CoRR abs/2102.12894 (2021) - [i10]Krishna Chaitanya, Ertunc Erdil, Neerav Karani, Ender Konukoglu:
Local contrastive loss with pseudo-label based self-training for semi-supervised medical image segmentation. CoRR abs/2112.09645 (2021) - [i9]Gustav Bredell, Ertunc Erdil, Bruno Weber, Ender Konukoglu:
Wiener Guided DIP for Unsupervised Blind Image Deconvolution. CoRR abs/2112.10271 (2021) - 2020
- [c18]Marc Gantenbein, Ertunc Erdil, Ender Konukoglu:
RevPHiSeg: A Memory-Efficient Neural Network for Uncertainty Quantification in Medical Image Segmentation. UNSURE/GRAIL@MICCAI 2020: 13-22 - [c17]Anna Volokitin, Ertunc Erdil, Neerav Karani, Kerem Can Tezcan, Xiaoran Chen, Luc Van Gool, Ender Konukoglu:
Modelling the Distribution of 3D Brain MRI Using a 2D Slice VAE. MICCAI (7) 2020: 657-666 - [c16]Krishna Chaitanya, Ertunc Erdil, Neerav Karani, Ender Konukoglu:
Contrastive learning of global and local features for medical image segmentation with limited annotations. NeurIPS 2020 - [i8]Krishna Chaitanya, Ertunc Erdil, Neerav Karani, Ender Konukoglu:
Contrastive learning of global and local features for medical image segmentation with limited annotations. CoRR abs/2006.10511 (2020) - [i7]Ertunc Erdil, Krishna Chaitanya, Ender Konukoglu:
Unsupervised out-of-distribution detection using kernel density estimation. CoRR abs/2006.10712 (2020) - [i6]Anna Volokitin, Ertunc Erdil, Neerav Karani, Kerem Can Tezcan, Xiaoran Chen, Luc Van Gool, Ender Konukoglu:
Modelling the Distribution of 3D Brain MRI using a 2D Slice VAE. CoRR abs/2007.04780 (2020) - [i5]Marc Gantenbein, Ertunc Erdil, Ender Konukoglu:
RevPHiSeg: A Memory-Efficient Neural Network for Uncertainty Quantification in Medical Image Segmentation. CoRR abs/2008.06999 (2020)
2010 – 2019
- 2019
- [j7]Ertunc Erdil, Sinan Yildirim, Tolga Tasdizen, Müjdat Çetin:
Pseudo-Marginal MCMC Sampling for Image Segmentation Using Nonparametric Shape Priors. IEEE Trans. Image Process. 28(11): 5702-5715 (2019) - [c15]Ertunc Erdil, Ali Ozgur Argunsah, Tolga Tasdizen, Devrim Ünay, Müjdat Çetin:
Combining Nonparametric Spatial Context Priors With Nonparametric Shape Priors for Dendritic Spine Segmentation in 2-Photon Microscopy Images. ISBI 2019: 204-207 - [i4]Ertunc Erdil, Ali Ozgur Argunsah, Tolga Tasdizen, Devrim Ünay, Müjdat Çetin:
Combining nonparametric spatial context priors with nonparametric shape priors for dendritic spine segmentation in 2-phoyon microscopy images. CoRR abs/1901.02513 (2019) - 2018
- [j6]Fitsum Mesadi, Ertunc Erdil, Müjdat Çetin, Tolga Tasdizen:
Image Segmentation Using Disjunctive Normal Bayesian Shape and Appearance Models. IEEE Trans. Medical Imaging 37(1): 293-305 (2018) - [i3]Ertunc Erdil, Sinan Yildirim, Tolga Tasdizen, Müjdat Çetin:
Image Segmentation with Pseudo-marginal MCMC Sampling and Nonparametric Shape Priors. CoRR abs/1809.00488 (2018) - 2017
- [b1]Ertunç Erdil:
Bayesian methods for segmentation of objects from multimodal and complex shape densities using statistical shape priors (Çok doruklu ve karmaşık şekil dağılımlarından gelen nesnelerin istatistiksel şekil ön bilgisi kullanarak bölütlenmesi için Bayesçi yaklaşımlar). Sabancı University, Turkey, 2017 - [j5]Ertunc Erdil, Muhammad Usman Ghani, Lavdie Rada, Ali Ozgur Argunsah, Devrim Ünay, Tolga Tasdizen, Müjdat Çetin:
Nonparametric Joint Shape and Feature Priors for Image Segmentation. IEEE Trans. Image Process. 26(11): 5312-5323 (2017) - [c14]Ertunc Erdil, Fitsum Mesadi, Tolga Tasdizen, Müjdat Çetin:
Disjunctive Normal Shape Boltzmann Machine. ICASSP 2017: 2357-2361 - [c13]Naeimeh Atabakilachini, Ertunc Erdil, Ali Ozgur Argunsah, Lavdie Rada, Devrim Ünay, Müjdat Çetin:
Coupled shape priors for dynamic segmentation of dendritic spines. SIU 2017: 1-4 - [c12]Erdem Bocugoz, Ertunc Erdil, Ali Ozgur Argunsah, Devrim Ünay, Müjdat Çetin:
3B dendritic spine segmentation using nonparametric shape priors. SIU 2017: 1-4 - [c11]Navdar Karabulut, Ertunc Erdil, Müjdat Çetin:
A Markov Chain Monte Carlo based rigid image registration method. SIU 2017: 1-4 - [c10]Osman Berk Satir, Ipek Baz, Ertunc Erdil, Müjdat Çetin:
On comparison of different classification techniques for the fine-grained retail product recognition problem. SIU 2017: 1-4 - 2016
- [c9]Ertunc Erdil, Sinan Yildirim, Müjdat Çetin, Tolga Tasdizen:
MCMC Shape Sampling for Image Segmentation with Nonparametric Shape Priors. CVPR 2016: 411-419 - [c8]Muhammad Usman Ghani, Ertunç Erdil, Sümeyra Demir Kanik, Ali Özgür Argunsah, Anna Felicity Hobbiss, Inbal Israely, Devrim Ünay, Tolga Tasdizen, Müjdat Çetin:
Dendritic Spine Shape Analysis: A Clustering Perspective. ECCV Workshops (1) 2016: 256-273 - [c7]Ertunc Erdil, Lavdie Rada, Ali Ozgur Argunsah, Inbal Israely, Devrim Ünay, Tolga Tasdizen, Müjdat Çetin:
Nonparametric joint shape and feature priors for segmentation of dendritic spines. ISBI 2016: 343-346 - [i2]Muhammad Usman Ghani, Ertunc Erdil, Sumeyra Demir Kanik, Ali Ozgur Argunsah, Anna Felicity Hobbiss, Inbal Israely, Devrim Ünay, Tolga Tasdizen, Müjdat Çetin:
Dendritic Spine Shape Analysis: A Clustering Perspective. CoRR abs/1607.05523 (2016) - [i1]Ertunc Erdil, Sinan Yildirim, Müjdat Çetin, Tolga Tasdizen:
MCMC Shape Sampling for Image Segmentation with Nonparametric Shape Priors. CoRR abs/1611.03749 (2016) - 2015
- [c6]Ertunc Erdil, Ali Ozgur Argunsah, Tolga Tasdizen, Devrim Ünay, Müjdat Çetin:
A joint classification and segmentation approach for dendritic spine segmentation in 2-photon microscopy images. ISBI 2015: 797-800 - [c5]Bike Kilic, Lavdie Rada, Ertunc Erdil, Ali Ozgur Argunsah, Müjdat Çetin, Devrim Ünay:
Automated dendritic spine tracking on 2-photon microscopic images. SIU 2015: 1873-1876 - 2014
- [c4]Lavdie Rada, Ertunc Erdil, Ali Ozgur Argunsah, Devrim Ünay, Müjdat Çetin:
Automatic dendritic spine detection using multiscale dot enhancement filters and SIFT features. ICIP 2014: 26-30 - 2013
- [j4]Selim Mimaroglu, Ertunc Erdil:
An efficient and scalable family of algorithms for combining clusterings. Eng. Appl. Artif. Intell. 26(10): 2525-2539 (2013) - [c3]Ertunc Erdil, Ali Ozgur Argunsah, Devrim Ünay, Müjdat Çetin:
A watershed and active contours based method for dendritic spine segmentation in 2-photon microscopy images. SIU 2013: 1-4 - [c2]A. Murat Yagci, Ertunc Erdil, Ali Ozgur Argunsah, Devrim Ünay, Müjdat Çetin, Lale Akarun, Fikret Gürgen:
Biomedical image time series registration with particle filtering. SIU 2013: 1-4 - 2012
- [c1]Ertunc Erdil, A. Murat Yagci, Ali Ozgur Argunsah, Y. Ramiro-Cortes, Anna Felicity Hobbiss, Inbal Israely, Devrim Ünay:
A tool for automatic dendritic spine detection and analysis. Part I: Dendritic spine detection using multi-level region-based segmentation. IPTA 2012: 167-171 - 2011
- [j3]Selim Mimaroglu, Ertunc Erdil:
ASOD: Arbitrary shape object detection. Eng. Appl. Artif. Intell. 24(7): 1295-1299 (2011) - [j2]Selim Mimaroglu, Ertunc Erdil:
Combining multiple clusterings using similarity graph. Pattern Recognit. 44(3): 694-703 (2011) - 2010
- [j1]Selim Mimaroglu, Ertunc Erdil:
Obtaining better quality final clustering by merging a collection of clusterings. Bioinform. 26(20): 2645-2646 (2010)
Coauthor Index
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