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Generalised Dice Overlap as a Deep Learning Loss Function for Highly Unbalanced Segmentations
Lecture Notes in Computer Science, 2017Deep-learning has proved in recent years to be a powerful tool for image analysis and is now widely used to segment both 2D and 3D medical images. Deep-learning segmentation frameworks rely not only on the choice of network architecture but also on the ...
Carole H Sudre +2 more
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DICE: Leveraging Sparsification for Out-of-Distribution Detection
European Conference on Computer Vision, 2021Detecting out-of-distribution (OOD) inputs is a central challenge for safely deploying machine learning models in the real world. Previous methods commonly rely on an OOD score derived from the overparameterized weight space, while largely overlooking ...
Yiyou Sun, Yixuan Li
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Grasping the dice by dicing the grasp
Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453), 2004Many methods for generating and analyzing grasps have been developed in the recent years. They gave insight and comprehension of grasping with robot hands but many of them are rather complicated to implement and of high computational complexity.
Borst, C., Fischer, M., Hirzinger, G.
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DICE: Data Discovery by Example
Proceedings of the VLDB Endowment, 2021In order to conduct analytical tasks, data scientists often need to find relevant data from an avalanche of sources (e.g., data lakes, large organizational databases).
E. Rezig +6 more
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Rethinking Dice Loss for Medical Image Segmentation
Industrial Conference on Data Mining, 2020Deep learning has proved to be a powerful tool for medical image analysis in recent years. Data imbalance is a common problem in medical images. Dice Loss is widely used in medical image segmentation tasks to address the data imbalance problem.
Rongjian Zhao +6 more
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Science, 2006 The [covery][1] of the 30 June issue shows a board game called “Life Cycles.” Also shown are two dice. For those not familiar with dice, there are “proper” and “not proper” die. A proper die must have the sum of the numbers on opposite sides equal to seven.
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Optimizing the Dice Score and Jaccard Index for Medical Image Segmentation: Theory and Practice
International Conference on Medical Image Computing and Computer-Assisted Intervention, 2019The Dice score and Jaccard index are commonly used metrics for the evaluation of segmentation tasks in medical imaging. Convolutional neural networks trained for image segmentation tasks are usually optimized for (weighted) cross-entropy. This introduces
J. Bertels +6 more
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Diffusion-DICE: In-Sample Diffusion Guidance for Offline Reinforcement Learning
Neural Information Processing SystemsOne important property of DIstribution Correction Estimation (DICE) methods is that the solution is the optimal stationary distribution ratio between the optimized and data collection policy. In this work, we show that DICE-based methods can be viewed as
Liyuan Mao +4 more
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Nontransitive Random Variables and Nontransitive Dice
The American mathematical monthly, 2021We give an explicit geometric proof that for each n there exists a cycle of n independent random variables such that for each random variable from this cycle the probability that it takes a value smaller than the next random variable from the cycle is at
Andrzej Komisarski
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