Results 41 to 50 of about 103,215 (258)
Polyp Generalization via Diversifying Style at Feature-Level Space
Applied SciencesIn polyp segmentation, the latest notable topic revolves around polyp generalization, which aims to develop deep learning-based models capable of learning from single or multiple source domains and applying this knowledge to unseen datasets.
Sahadev Poudel, Sang-Woong Lee
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An Optimization-Based Meta-Learning Model for MRI Reconstruction with Diverse Dataset
Journal of Imaging, 2021 This work aims at developing a generalizable Magnetic Resonance Imaging (MRI) reconstruction method in the meta-learning framework. Specifically, we develop a deep reconstruction network induced by a learnable optimization algorithm (LOA) to solve the ...
Wanyu Bian +3 more
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Cerebellar ataxia after pediatric brain tumor treatment can cause persistent gait, balance, and speech impairment, yet no established rehabilitation strategy exists. Somato‐cognitive coordination therapy (SCCT) is a virtual reality–guided intervention designed to promote sensorimotor integration through visually constrained reaching
Masanobu Takeuchi +10 more
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Ladder Curriculum Learning for Domain Generalization in Cross-Domain Classification
IEEE AccessDomain generalization seeks to acquire a domain-invariant representation from various source domains, thereby enabling a model to achieve robust generalization across previously unseen target domains. Most existing domain generalization methods for cross-
Xiaoshun Wang, Sibei Luo, Yiming Gao
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Generalizing domain theory [PDF]
, 1998 Domain theory began in an attempt to provide mathematical models for high-level programming languages, an area where it has proved to be particularly useful. It is perhaps the most widely-used method for devising semantic models for such languages. This paper is a survey of some generalizations of domain theory that have arisen in efforts to solve ...
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On Calibration and Out-of-domain Generalization
CoRR, 2021 24 pages, 6 figures. Published at NeurIPS 2021. Change log for each version: v2 - major revision, main additions are a trainable calibration loss (CLOvE) and experiments with fine-tuning. v3 - minor revision, main changes are added background material and technical details to the supplementary, and a fix to lemma 1.
Yoav Wald +3 more
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Introduction The use of herbal medical preparation (HMP) is rising among pediatric oncology patients, often to manage treatment‐related symptoms. Their effectiveness remains uncertain, and the risk of herb–drug interactions is underestimated.
Orianne Mahot +6 more
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FSN: Feature Shift Network for Load-Domain (LD) Domain Generalization
Applied SciencesConventional deep learning methods for fault detection often assume that the training and the testing sets share the same fault domain spaces. However, some fault patterns are rare, and many real-world faults have not appeared in the training set.
Heng Chen +3 more
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Cross-domain Ensemble Distillation for Domain Generalization
, 2022 Accepted to ECCV 2022.
Kyungmoon Lee, Sungyeon Kim, Suha Kwak
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Pediatric radiation therapy presents unique challenges compared to adult treatments, including those of immobilization, potential need for sedation, and the critical importance of accurate, reproducible positioning. Additionally, heightened attention to imaging doses is necessary to minimize long‐term toxicity in survivors.
Parham Alaei +17 more
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