Results 31 to 40 of about 283,560 (267)
Cascaded multiple classifiers for secondary structure prediction [PDF]
Protein Science, 2000 AbstractWe describe a new classifier for protein secondary structure prediction that is formed by cascading together different types of classifiers using neural networks and linear discrimination. The new classifier achieves an accuracy of 76.7% (assessed by a rigorous full Jack‐knife procedure) on a new nonredundant dataset of 496 nonhomologous ...
Ouali, Mohammed, King, Ross D.
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Cascade Forest-Based Model for Prediction of RNA Velocity
Molecules, 2022 In recent years, single-cell RNA sequencing technology (scRNA-seq) has developed rapidly and has been widely used in biological and medical research, such as in expression heterogeneity and transcriptome dynamics of single cells. The investigation of RNA
Zhiliang Zeng +4 more
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Cascade-LSTM: Predicting Information Cascades using Deep Neural Networks
, 2020 Predicting the flow of information in dynamic social environments is relevant to many areas of the contemporary society, from disseminating health care messages to meme tracking. While predicting the growth of information cascades has been successfully addressed in diverse social platforms, predicting the temporal and topological structure of ...
Horawalavithana, Sameera +2 more
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Energies, 2022 Accurate wind speed prediction is a premise that guarantees the reliable operation of the power grid. This study presents a combined prediction model that integrates data preprocessing, cascade optimization, and deep learning prediction to improve ...
Kui Yang +5 more
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The theoretical development of the cascade model excimer laser irradiation on the organ of vision
Oftalʹmologiâ, 2014 Authors analyzed the baseline (Pershin K. B., 2000) and advanced (trubilin V. N Pozharitskii M. D., 2011) theoretical model of the cascade excimer laser effects on eyesight.the analysis indicates a lack of elaboration of issues related to the cascade of «
V. N. Trubilin +3 more
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Structured Prediction Cascades
, 2012 Structured prediction tasks pose a fundamental trade-off between the need for model complexity to increase predictive power and the limited computational resources for inference in the exponentially-sized output spaces such models require. We formulate and develop the Structured Prediction Cascade architecture: a sequence of increasingly complex models
Weiss, David +2 more
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PredCNN: Predictive Learning with Cascade Convolutions [PDF]
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018 Predicting future frames in videos remains an unsolved but challenging problem. Mainstream recurrent models suffer from huge memory usage and computation cost, while convolutional models are unable to effectively capture the temporal dependencies between consecutive video frames.
Ziru Xu +3 more
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IEEE Access, 2020 Deep learning has been a widely adopted approach to achieve the remaining useful life prediction (RUL) of rolling bearing. However, the architectures of the current proposed deep learning approaches are limited and the prediction result is less stable on
Qiong Wu, Changsheng Zhang
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AIP Advances, 2022 The generalization ability and robustness of data-driven models deteriorate when samples are scarce or input features are outside the training sample space.
Yunfei Li +4 more
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Helicity cascades in rotating turbulence [PDF]
, 2008 The effect of helicity (velocity-vorticity correlations) is studied in direct numerical simulations of rotating turbulence down to Rossby numbers of 0.02.
A. Craya +8 more
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