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Advancing opportunities for children’s informal STEM learning transfer through parent–child narrative reflection
Advancing opportunities for children’s informal STEM learning transfer through parent–child narrative reflection
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Advancing opportunities for children’s informal STEM learning transfer through parent–child narrative reflection

Marcus, Maria ; Tõugu, Pirko ; Haden, Catherine A. ; Uttal, David H.

Child development, 2021-09, Vol.92 (5), p.e1075-e1084 [Periódico revisado por pares]

Ann Arbor: Wiley

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Patient‐specific transfer learning for auto‐segmentation in adaptive 0.35 T MRgRT of prostate cancer: a bi‐centric evaluation
Patient‐specific transfer learning for auto‐segmentation in adaptive 0.35 T MRgRT of prostate cancer: a bi‐centric evaluation
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Patient‐specific transfer learning for auto‐segmentation in adaptive 0.35 T MRgRT of prostate cancer: a bi‐centric evaluation

Kawula, Maria ; Hadi, Indrawati ; Nierer, Lukas ; Vagni, Marica ; Cusumano, Davide ; Boldrini, Luca ; Placidi, Lorenzo ; Corradini, Stefanie ; Belka, Claus ; Landry, Guillaume ; Kurz, Christopher

Medical physics (Lancaster), 2023-03, Vol.50 (3), p.1573-1585 [Periódico revisado por pares]

United States

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Weakly supervised breast lesion detection in DCE‐MRI using self‐transfer learning
Weakly supervised breast lesion detection in DCE‐MRI using self‐transfer learning
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Weakly supervised breast lesion detection in DCE‐MRI using self‐transfer learning

Sun, Rong ; Zhang, Xiaobing ; Xie, Yuanzhong ; Nie, Shengdong

Medical physics (Lancaster), 2023-08, Vol.50 (8), p.4960-4972 [Periódico revisado por pares]

United States

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Ground motion models for regions with limited data: Data‐driven approach
Ground motion models for regions with limited data: Data‐driven approach
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Ground motion models for regions with limited data: Data‐driven approach

Sreenath, Vemula ; Basu, Jahnabi ; Raghukanth, S. T. G.

Earthquake engineering & structural dynamics, 2024-03, Vol.53 (3), p.1363-1375 [Periódico revisado por pares]

Bognor Regis: Wiley Subscription Services, Inc

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5
Optimizing the transfer‐learning with pretrained deep convolutional neural networks for first stage breast tumor diagnosis using breast ultrasound visual images
Optimizing the transfer‐learning with pretrained deep convolutional neural networks for first stage breast tumor diagnosis using breast ultrasound visual images
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Optimizing the transfer‐learning with pretrained deep convolutional neural networks for first stage breast tumor diagnosis using breast ultrasound visual images

Saba, Tanzila ; Abunadi, Ibrahim ; Sadad, Tariq ; Khan, Amjad Rehman ; Bahaj, Saeed Ali

Microscopy research and technique, 2022-04, Vol.85 (4), p.1444-1453 [Periódico revisado por pares]

Hoboken, USA: John Wiley & Sons, Inc

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Transfer learning meets sales engagement email classification: Evaluation, analysis, and strategies
Transfer learning meets sales engagement email classification: Evaluation, analysis, and strategies
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Transfer learning meets sales engagement email classification: Evaluation, analysis, and strategies

Liu, Yong ; Dmitriev, Pavel ; Huang, Yifei ; Brooks, Andrew ; Dong, Li ; Liang, Mengyue ; Boshernitzan, Zvi ; Cao, Jiwei ; Nguy, Bobby

Concurrency and computation, 2022-04, Vol.34 (8), p.n/a [Periódico revisado por pares]

Hoboken, USA: John Wiley & Sons, Inc

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Transfer learning and fine‐tuned transfer learning methods' effectiveness analyse in the CNN‐based deep learning models
Transfer learning and fine‐tuned transfer learning methods' effectiveness analyse in the CNN‐based deep learning models
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Transfer learning and fine‐tuned transfer learning methods' effectiveness analyse in the CNN‐based deep learning models

Öztürk, Celal ; Taşyürek, Murat ; Türkdamar, Mehmet Uğur

Concurrency and computation, 2023-02, Vol.35 (4), p.n/a [Periódico revisado por pares]

Hoboken: Wiley Subscription Services, Inc

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An experimental comparison of the widely used pre‐trained deep neural networks for image classification tasks towards revealing the promise of transfer‐learning
An experimental comparison of the widely used pre‐trained deep neural networks for image classification tasks towards revealing the promise of transfer‐learning
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An experimental comparison of the widely used pre‐trained deep neural networks for image classification tasks towards revealing the promise of transfer‐learning

Kabakus, Abdullah Talha ; Erdogmus, Pakize

Concurrency and computation, 2022-11, Vol.34 (24), p.n/a [Periódico revisado por pares]

Hoboken, USA: John Wiley & Sons, Inc

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9
Surface crack detection based on image stitching and transfer learning with pretrained convolutional neural network
Surface crack detection based on image stitching and transfer learning with pretrained convolutional neural network
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Surface crack detection based on image stitching and transfer learning with pretrained convolutional neural network

Wu, Lijun ; Lin, Xu ; Chen, Zhicong ; Lin, Peijie ; Cheng, Shuying

Structural control and health monitoring, 2021-08, Vol.28 (8), p.n/a [Periódico revisado por pares]

Pavia: Wiley Subscription Services, Inc

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10
Deep transfer learning of structural magnetic resonance imaging fused with blood parameters improves brain age prediction
Deep transfer learning of structural magnetic resonance imaging fused with blood parameters improves brain age prediction
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Deep transfer learning of structural magnetic resonance imaging fused with blood parameters improves brain age prediction

Ren, Bingyu ; Wu, Yingtong ; Huang, Liumei ; Zhang, Zhiguo ; Huang, Bingsheng ; Zhang, Huajie ; Ma, Jinting ; Li, Bing ; Liu, Xukun ; Wu, Guangyao ; Zhang, Jian ; Shen, Liming ; Liu, Qiong ; Ni, Jiazuan

Human brain mapping, 2022-04, Vol.43 (5), p.1640-1656 [Periódico revisado por pares]

Hoboken, USA: John Wiley & Sons, Inc

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