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Automatic detection of photovoltaic module defects in infrared images with isolated and develop-model transfer deep learning
Automatic detection of photovoltaic module defects in infrared images with isolated and develop-model transfer deep learning
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Automatic detection of photovoltaic module defects in infrared images with isolated and develop-model transfer deep learning

Akram, M. Waqar ; Li, Guiqiang ; Jin, Yi ; Chen, Xiao ; Zhu, Changan ; Ahmad, Ashfaq

Solar energy, 2020-03, Vol.198, p.175-186 [Periódico revisado por pares]

New York: Elsevier Ltd

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3-D Deep Learning Approach for Remote Sensing Image Classification
3-D Deep Learning Approach for Remote Sensing Image Classification
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3-D Deep Learning Approach for Remote Sensing Image Classification

Ben Hamida, Amina ; Benoit, Alexandre ; Lambert, Patrick ; Ben Amar, Chokri

IEEE transactions on geoscience and remote sensing, 2018-08, Vol.56 (8), p.4420-4434 [Periódico revisado por pares]

New York: IEEE

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3
Physics-informed multi-LSTM networks for metamodeling of nonlinear structures
Physics-informed multi-LSTM networks for metamodeling of nonlinear structures
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Physics-informed multi-LSTM networks for metamodeling of nonlinear structures

Zhang, Ruiyang ; Liu, Yang ; Sun, Hao

Computer methods in applied mechanics and engineering, 2020-09, Vol.369, p.113226, Article 113226 [Periódico revisado por pares]

Amsterdam: Elsevier B.V

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4
Deep Learning-Based Imbalanced Data Classification for Drug Discovery
Deep Learning-Based Imbalanced Data Classification for Drug Discovery
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Deep Learning-Based Imbalanced Data Classification for Drug Discovery

Korkmaz, Selçuk

Journal of chemical information and modeling, 2020-09, Vol.60 (9), p.4180-4190 [Periódico revisado por pares]

United States: American Chemical Society

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5
KIKI‐net: cross‐domain convolutional neural networks for reconstructing undersampled magnetic resonance images
KIKI‐net: cross‐domain convolutional neural networks for reconstructing undersampled magnetic resonance images
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KIKI‐net: cross‐domain convolutional neural networks for reconstructing undersampled magnetic resonance images

Eo, Taejoon ; Jun, Yohan ; Kim, Taeseong ; Jang, Jinseong ; Lee, Ho‐Joon ; Hwang, Dosik

Magnetic resonance in medicine, 2018-11, Vol.80 (5), p.2188-2201 [Periódico revisado por pares]

United States: Wiley Subscription Services, Inc

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6
PET image denoising using unsupervised deep learning
PET image denoising using unsupervised deep learning
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PET image denoising using unsupervised deep learning

Cui, Jianan ; Gong, Kuang ; Guo, Ning ; Wu, Chenxi ; Meng, Xiaxia ; Kim, Kyungsang ; Zheng, Kun ; Wu, Zhifang ; Fu, Liping ; Xu, Baixuan ; Zhu, Zhaohui ; Tian, Jiahe ; Liu, Huafeng ; Li, Quanzheng

European journal of nuclear medicine and molecular imaging, 2019-12, Vol.46 (13), p.2780-2789 [Periódico revisado por pares]

Berlin/Heidelberg: Springer Berlin Heidelberg

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7
Evaluation of Different Machine Learning Methods and Deep-Learning Convolutional Neural Networks for Landslide Detection
Evaluation of Different Machine Learning Methods and Deep-Learning Convolutional Neural Networks for Landslide Detection
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Evaluation of Different Machine Learning Methods and Deep-Learning Convolutional Neural Networks for Landslide Detection

Ghorbanzadeh, Omid ; Blaschke, Thomas ; Gholamnia, Khalil ; Meena, Sansar ; Tiede, Dirk ; Aryal, Jagannath

Remote sensing (Basel, Switzerland), 2019-01, Vol.11 (2), p.196 [Periódico revisado por pares]

Basel: MDPI AG

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8
Accurate cloud detection in high-resolution remote sensing imagery by weakly supervised deep learning
Accurate cloud detection in high-resolution remote sensing imagery by weakly supervised deep learning
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Accurate cloud detection in high-resolution remote sensing imagery by weakly supervised deep learning

Li, Yansheng ; Chen, Wei ; Zhang, Yongjun ; Tao, Chao ; Xiao, Rui ; Tan, Yihua

Remote sensing of environment, 2020-12, Vol.250, p.112045, Article 112045 [Periódico revisado por pares]

New York: Elsevier Inc

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9
Novel Ensemble Approach of Deep Learning Neural Network (DLNN) Model and Particle Swarm Optimization (PSO) Algorithm for Prediction of Gully Erosion Susceptibility
Novel Ensemble Approach of Deep Learning Neural Network (DLNN) Model and Particle Swarm Optimization (PSO) Algorithm for Prediction of Gully Erosion Susceptibility
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Novel Ensemble Approach of Deep Learning Neural Network (DLNN) Model and Particle Swarm Optimization (PSO) Algorithm for Prediction of Gully Erosion Susceptibility

Band, Shahab S ; Janizadeh, Saeid ; Chandra Pal, Subodh ; Saha, Asish ; Chakrabortty, Rabin ; Shokri, Manouchehr ; Mosavi, Amirhosein

Sensors (Basel, Switzerland), 2020-09, Vol.20 (19), p.5609 [Periódico revisado por pares]

Switzerland: MDPI AG

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10
Multimodal Brain Tumor Classification Using Deep Learning and Robust Feature Selection: A Machine Learning Application for Radiologists
Multimodal Brain Tumor Classification Using Deep Learning and Robust Feature Selection: A Machine Learning Application for Radiologists
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Multimodal Brain Tumor Classification Using Deep Learning and Robust Feature Selection: A Machine Learning Application for Radiologists

Khan, Muhammad Attique ; Ashraf, Imran ; Alhaisoni, Majed ; Damaševičius, Robertas ; Scherer, Rafal ; Rehman, Amjad ; Bukhari, Syed Ahmad Chan

Diagnostics (Basel), 2020-08, Vol.10 (8), p.565 [Periódico revisado por pares]

Basel: MDPI AG

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