Results 11 to 20 of about 1,979,450 (271)
Progressive Transfer Learning [PDF]
IEEE Transactions on Image Processing, 2022 10 pages, 4 figures, journel verison of our published short paper on ...
Zhengxu Yu +5 more
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Inteligencia Artificial, 2022 Deep Learning and transfer learning models are being used to generate time series forecasts; however, there is scarce evidence about their performance prediction that it is more evident for monthly time series.
Martín Solís +1 more
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Quantum deep transfer learning
New Journal of Physics, 2021 Quantum machine learning (QML) has aroused great interest because it has the potential to speed up the established classical machine learning processes.
Longhan Wang, Yifan Sun, Xiangdong Zhang
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Artificial Intelligence, 2014 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
ZHAO, Peilin +3 more
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Factors influencing the learning transfer of nursing students in a non-face-to-face educational environment during the COVID-19 pandemic in Korea: a cross-sectional study using structural equation modeling [PDF]
Journal of Educational Evaluation for Health Professions, 2023 Purpose The aim of this study was to identify factors influencing the learning transfer of nursing students in a non-face-to-face educational environment through structural equation modeling and suggest ways to improve the transfer of learning.
Geun Myun Kim +2 more
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'We nicked stuff from all over the place': policy transfer or muddling through? [PDF]
, 2008 This article explores current thinking about policy learning and transfer, using recent work on the 'Americanisation' of UK active labour market policies as a focus of discussion. While it is clear that the UK has learned from the US in certain respects,
Dwyer, PJ, Ellison, N
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Komputika, 2023 Deep learning is a branch of machine learning with many highly successful applications. One application of deep learning is image classification using the Convolutional Neural Network (CNN) algorithm. Large image data is required to classify images with
Muhammad Daffa Arviano Putra +4 more
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Fuzzy Inference and Manifold Regularization Combined Feature Transfer Learning
Jisuanji kexue yu tansuo, 2020 Transfer learning leverages the rich data in the source domain to provide support for building accurate models in the target domain. Feature transfer learning is a kind of widely studied technology in transfer learning, but the existing feature transfer ...
SONG Yixuan, DENG Zhaohong, QIN Bin
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Frontiers in Psychology, 2017 The current experiment investigated generalizability of motor learning in proximal versus distal effectors in upper extremities. Twenty-eight participants were divided into three groups: training proximal effectors, training distal effectors, and no ...
Tore K. Aune +3 more
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Measuring learning transfer in a financial institution (Part 2)
SA Journal of Industrial Psychology, 2006 The purpose of this study was to identify learning transfer variables impacting on learning transfer using the Learning Transfer System Inventory (LTSI).
W J Coetsee, R Eiselen
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