Results 31 to 40 of about 10,380,352 (315)
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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Transfer Learning in Magnetic Resonance Brain Imaging: A Systematic Review
Journal of Imaging, 2021 (1) Background: Transfer learning refers to machine learning techniques that focus on acquiring knowledge from related tasks to improve generalization in the tasks of interest.
Juan Miguel Valverde +6 more
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Impact of intercity low-carbon technology transfer on carbon emission reduction in China:Based on the “dichotomy” of knowledge learning and technology learning [PDF]
Ziyuan Kexue, 2023 [Objective] Increasing the transfer of low-carbon technology (LCT) is the key to narrowing the gap in LCT between regions and improving the overall level of low-carbon technology of China.
SHANG Yongmin, MI Zefeng, ZHOU Can, LIN Lan
doaj +1 more source
Artificial Intelligence, 2014 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
ZHAO, Peilin +3 more
openaire +2 more sources
AdapterFusion: Non-Destructive Task Composition for Transfer Learning [PDF]
Conference of the European Chapter of the Association for Computational Linguistics, 2020 Sequential fine-tuning and multi-task learning are methods aiming to incorporate knowledge from multiple tasks; however, they suffer from catastrophic forgetting and difficulties in dataset balancing.
Jonas Pfeiffer +4 more
semanticscholar +1 more source
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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Mapping single-cell data to reference atlases by transfer learning
Nature Biotechnology, 2021 Large single-cell atlases are now routinely generated to serve as references for analysis of smaller-scale studies. Yet learning from reference data is complicated by batch effects between datasets, limited availability of computational resources and ...
M. Lotfollahi +12 more
semanticscholar +1 more source
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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IEEE Transactions on Neural Networks and Learning Systems, 2023 Over the last decade, transfer learning has attracted a great deal of attention as a new learning paradigm, based on which fault diagnosis (FD) approaches have been intensively developed to improve the safety and reliability of modern automation systems.
Hongtian Chen +4 more
semanticscholar +1 more source