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Found 5 papers, 3 papers with code
Selective Prediction for Semantic Segmentation using Post-Hoc Confidence Estimation and Its Performance under Distribution Shift
Our findings show that post-hoc confidence estimators offer a cost-effective approach to reducing the impacts of distribution shift.
Deep-learning-based Early Fixing for Gas-lifted Oil Production Optimization: Supervised and Weakly-supervised Approaches
Maximizing oil production from gas-lifted oil wells entails solving Mixed-Integer Linear Programs (MILPs).
Does pre-training on brain-related tasks results in better deep-learning-based brain age biomarkers?
Brain age prediction using neuroimaging data has shown great potential as an indicator of overall brain health and successful aging, as well as a disease biomarker.
Graph Neural Networks for the Offline Nanosatellite Task Scheduling Problem
This study examines the use of GNNs in this context, which has been effectively applied to optimization problems such as the traveling salesman, scheduling, and facility placement problems.
Combinatorial Optimization
Explainable Artificial Intelligence (XAI)
+1
Towards fully automated deep-learning-based brain tumor segmentation: is brain extraction still necessary?
Our experiments show that the choice of a BE method can compromise up to 15. 7% of the tumor segmentation performance.
