Results 21 to 30 of about 63,859 (268)
Radiation treatment dropouts-Pitfalls and solutions: A retrospective observational study
Cancer Research, Statistics, and Treatment, 2023 Background: Interruptions in radiation treatment are known to have a deleterious effect on oncologic outcomes,specifically, an increase in tumor recurrence and decrease in cancer cure rate.
Kanhu Charan Patro +8 more
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, 2017 Dropout is used as a practical tool to obtain uncertainty estimates in large vision models and reinforcement learning (RL) tasks. But to obtain well-calibrated uncertainty estimates, a grid-search over the dropout probabilities is necessary - a prohibitive operation with large models, and an impossible one with RL.
Gal, Y, Hron, J, Kendall, A
openaire +4 more sources
Proceedings of the AAAI Conference on Artificial Intelligence, 2019 Dropout is often used in deep neural networks to prevent over-fitting. Conventionally, dropout training invokes random drop of nodes from the hidden layers of a Neural Network. It is our hypothesis that a guided selection of nodes for intelligent dropout can lead to better generalization as compared to the traditional dropout.
Rohit Keshari +2 more
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Nordic Journal of Vocational Education and Training, 2020 In Sweden, many students start but do not graduate from upper secondary school despite preventive efforts. The reasons for students dropping out of school have been examined and opposed, but there is still more to be done.
Ulrika Gidlund
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Evaluation of reasons of glaucoma treatment dropouts in a health-care center
Journal of Clinical Ophthalmology and Research, 2022 Aims: The aim of this study is to evaluate the reasons of dropout in glaucoma patients in a health-care center. Materials and Methods: A cross-sectional study was carried out among 135 glaucoma patients assessed from January 2013 to January 2016 and lost
Surohi Shah +5 more
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2017 IEEE International Conference on Computer Vision (ICCV), 2017 Dropout is a very effective way of regularizing neural networks. Stochastically "dropping out" units with a certain probability discourages over-specific co-adaptations of feature detectors, preventing overfitting and improving network generalization.
Pietro Morerio +4 more
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Stochastic Analysis of the RT-PCR Process in Single-Cell RNA-Seq
Mathematics, 2021 The single-cell RNA-seq allows exploring the transcriptome for one cell at a time. By doing so, cellular regulation is pictured. One limitation is the dropout events phenomenon, where a gene is observed at a low or moderate expression level in one cell ...
Aarón Vázquez-Jiménez +1 more
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IEEE Transactions on Neural Networks and Learning Systems, 2018 Accepted by ...
Xu Shen 0001 +4 more
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Student throughput variables and properties: Varying cohort sizes
South African Journal of Science, 2017 A recent research paper described how student throughput variables and properties combine to explain the behaviour of stationary or simplified throughput systems.
Lucas C.A. Stoop
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Data Gap Classification for Terrestrial Laser Scanning-Derived Digital Elevation Models
ISPRS International Journal of Geo-Information, 2020 Extensive gaps in terrestrial laser scanning (TLS) point cloud data can primarily be classified into two categories: occlusions and dropouts. These gaps adversely affect derived products such as 3D surface models and digital elevation models (DEMs ...
Matthew S. O’Banion +3 more
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