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For semantic segmentation, label probabilities are often uncalibrated as they are typically only the by-product of a segmentation task.
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Combination strategies in multi-atlas image segmentation: application to brain MR data
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Patch-based segmentation using expert priors: Application to hippocampus and ventricle segmentation
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Multi-atlas segmentation with joint label fusion
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Fully convolutional networks for semantic segmentation
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Obtaining well calibrated probabilities using Bayesian binning
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Holger Caesar, Jasper Uijlings, and Vittorio Ferrari · 2018
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Recent advances in convolutional neural networks
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Trainable calibration measures for neural networks from kernel mean embeddings
Aviral Kumar, Sunita Sarawagi, and Ujjwal Jain · 2018
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Dirichlet-based Gaussian processes for large-scale calibrated classification
Dimitrios Milios, Raffaello Camoriano, Pietro Michiardi, Lorenzo Rosasco, and Maurizio Filippone · 2018
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Attended temperature scaling: A practical approach for calibrating deep neural networks
Azadeh Sadat Mozafari, Hugo Siqueira Gomes, Wilson Leão, Steeven Janny, and Christian Gagné · 2018
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Mahdi Pakdaman Naeini, Gregory Cooper, and Milos Hauskrecht · 2015
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End to end learning for self-driving cars
Mariusz Bojarski, Davide Del Testa, Daniel Dworakowski, Bernhard Firner, Beat Flepp, Prasoon Goyal, Lawrence D Jackel, Mathew Monfort, Urs Muller, Jiakai Zhang, et al · 2016
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3D U-Net: learning dense volumetric segmentation from sparse annotation
Özgün Çiçek, Ahmed Abdulkadir, Soeren S Lienkamp, Thomas Brox, and Olaf Ronneberger · 2016
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Dropout as a Bayesian approximation: Representing model uncertainty in deep learning
Yarin Gal and Zoubin Ghahramani · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Autoencoder trees
Ozan Irsoy and Ethem Alpaydin · 2016
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Simple and scalable predictive uncertainty estimation using deep ensembles
Balaji Lakshminarayanan, Alexander Pritzel, and Charles Blundell · 2016
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Non-parametric Bayesian isotonic calibration: Fighting over-confidence in binary classification
Mari-Liis Allikivi and Meelis Kull · 2019
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Votenet: A deep learning label fusion method for multi-atlas segmentation
Zhipeng Ding, Xu Han, and Marc Niethammer · 2019
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A Bayesian neural net to segment images with uncertainty estimates and good calibration
Rohit Jena and Suyash P Awate · 2019
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Byeongmoon Ji, Hyemin Jung, Jihyeun Yoon, Kyungyul Kim, and Younghak Shin · 2019
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Beyond temperature scaling: Obtaining well-calibrated multi-class probabilities with Dirichlet calibration
Meelis Kull, Miquel Perello Nieto, Markus Kängsepp, Telmo Silva Filho, Hao Song, and Peter Flach · 2019
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Overfitting of neural nets under class imbalance: Analysis and improvements for segmentation
Zeju Li, Konstantinos Kamnitsas, and Ben Glocker · 2019
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A simple baseline for Bayesian uncertainty in deep learning
Wesley J Maddox, Pavel Izmailov, Timur Garipov, Dmitry P Vetrov, and Andrew Gordon Wilson · 2019
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Confidence calibration and predictive uncertainty estimation for deep medical image segmentation
Alireza Mehrtash, William M Wells III, Clare M Tempany, Purang Abolmaesumi, and Tina Kapur · 2019
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Measuring calibration in deep learning
Jeremy Nixon, Mike Dusenberry, Linchuan Zhang, Ghassen Jerfel, and Dustin Tran · 2019
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Calibrating deep convolutional gaussian processes
Gia-Lac Tran, Edwin V Bonilla, John Cunningham, Pietro Michiardi, and Maurizio Filippone · 2019
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Improving multi-atlas segmentation by convolutional neural network based patch error estimation
Long Xie, Jiancong Wang, Mengjin Dong, David A Wolk, and Paul A Yushkevich · 2019
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Votenet+: An improved deep learning label fusion method for multi-atlas segmentation
Zhipeng Ding, Xu Han, and Marc Niethammer · 2020
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Davood Karimi and Ali Gholipour · 2020
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Calibration of deep probabilistic models with decoupled Bayesian neural networks
Juan Maroñas, Roberto Paredes, and Daniel Ramos · 2020
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Calibrating deep neural networks using focal loss
Jishnu Mukhoti, Viveka Kulharia, Amartya Sanyal, Stuart Golodetz, Philip HS Torr, and Puneet K Dokania · 2020
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Intra order-preserving functions for calibration of multi-class neural networks
Amir Rahimi, Amirreza Shaban, Ching-An Cheng, Byron Boots, and Richard Hartley · 2020
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Non-parametric calibration for classification
Jonathan Wenger, Hedvig Kjellström, and Rudolph Triebel · 2020
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Mix-n-match: Ensemble and compositional methods for uncertainty calibration in deep learning
Jize Zhang, Bhavya Kailkhura, and T Han · 2020
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