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Quantum Adversarial Transfer Learning
Entropy, 2023 Adversarial transfer learning is a machine learning method that employs an adversarial training process to learn the datasets of different domains. Recently, this method has attracted attention because it can efficiently decouple the requirements of ...
Longhan Wang, Yifan Sun, Xiangdong Zhang
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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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ST-Adapter: Parameter-Efficient Image-to-Video Transfer Learning for Action Recognition [PDF]
Neural Information Processing Systems, 2022 Capitalizing on large pre-trained models for various downstream tasks of interest have recently emerged with promising performance. Due to the ever-growing model size, the standard full fine-tuning based task adaptation strategy becomes prohibitively ...
Junting Pan +4 more
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Covid-19: automatic detection from X-ray images utilizing transfer learning with convolutional neural networks [PDF]
Physical and Engineering Sciences in Medicine, 2020 In this study, a dataset of X-ray images from patients with common bacterial pneumonia, confirmed Covid-19 disease, and normal incidents, was utilized for the automatic detection of the Coronavirus disease.
Ioannis D. Apostolopoulos +1 more
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A Review of Deep Transfer Learning and Recent Advancements [PDF]
Technologies, 2022 Deep learning has been the answer to many machine learning problems during the past two decades. However, it comes with two significant constraints: dependency on extensive labeled data and training costs.
Mohammadreza Iman +2 more
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Transfer Learning Under High-Dimensional Generalized Linear Models [PDF]
Journal of the American Statistical Association, 2021 In this work, we study the transfer learning problem under high-dimensional generalized linear models (GLMs), which aim to improve the fit on target data by borrowing information from useful source data.
Ye Tian, Yang Feng
semanticscholar +1 more source
Journal of Ethnic Foods, 2022 The increased frequency of extreme climate-induced natural disasters (floods, cyclones, mud slides, heat waves, droughts), attributed to climate change, is causing stress to already vulnerable livelihoods by affecting both tangible and intangible ...
Vimbainashe Prisca Dembedza +3 more
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A Comprehensive Survey on Transfer Learning [PDF]
Proceedings of the IEEE, 2019 Transfer learning aims at improving the performance of target learners on target domains by transferring the knowledge contained in different but related source domains.
Fuzhen Zhuang +7 more
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Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning [PDF]
IEEE Transactions on Medical Imaging, 2016 Remarkable progress has been made in image recognition, primarily due to the availability of large-scale annotated datasets and deep convolutional neural networks (CNNs).
Hoo-Chang Shin +8 more
semanticscholar +1 more source
Energies, 2021 The intermittent nature of renewable sources, such as solar and wind, leads to the need for a hybrid renewable energy system (HRES) that can provide uninterrupted and reliable energy to a remote and off-grid location with the use of a biogas generator ...
Vijay Mudgal +6 more
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