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Structural Damage Identification of Composite Rotors Based on Fully Connected Neural Networks and Convolutional Neural Networks
Structural Damage Identification of Composite Rotors Based on Fully Connected Neural Networks and Convolutional Neural Networks
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Structural Damage Identification of Composite Rotors Based on Fully Connected Neural Networks and Convolutional Neural Networks

Scholz, Veronika ; Winkler, Peter ; Hornig, Andreas ; Gude, Maik ; Filippatos, Angelos

Sensors (Basel, Switzerland), 2021-03, Vol.21 (6), p.2005 [Periódico revisado por pares]

Switzerland: MDPI AG

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2
Memory-based pruning of deep neural networks for IoT devices applied to flood detection
Memory-based pruning of deep neural networks for IoT devices applied to flood detection
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Memory-based pruning of deep neural networks for IoT devices applied to flood detection

Francisco Erivaldo Fernandes Junior Luis Gustavo Nonato; Caetano Mazzoni Ranieri; Jó Ueyama

Sensors Basel : MDPI v. 21, n. 22, p. 1-18, 2021

Basel 2021

Localização: ICMC - Inst. Ciên. Mat. Computação    (PROD-3049890 )(Acessar)

3
Identification of Road-Surface Type Using Deep Neural Networks for Friction Coefficient Estimation
Identification of Road-Surface Type Using Deep Neural Networks for Friction Coefficient Estimation
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Identification of Road-Surface Type Using Deep Neural Networks for Friction Coefficient Estimation

Šabanovič, Eldar ; Žuraulis, Vidas ; Prentkovskis, Olegas ; Skrickij, Viktor

Sensors (Basel, Switzerland), 2020-01, Vol.20 (3), p.612 [Periódico revisado por pares]

Switzerland: MDPI AG

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4
Bearing Fault Diagnosis with a Feature Fusion Method Based on an Ensemble Convolutional Neural Network and Deep Neural Network
Bearing Fault Diagnosis with a Feature Fusion Method Based on an Ensemble Convolutional Neural Network and Deep Neural Network
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Bearing Fault Diagnosis with a Feature Fusion Method Based on an Ensemble Convolutional Neural Network and Deep Neural Network

Li, Hongmei ; Huang, Jinying ; Ji, Shuwei

Sensors (Basel, Switzerland), 2019-04, Vol.19 (9), p.2034 [Periódico revisado por pares]

Switzerland: MDPI AG

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5
Classifying Parkinson's Disease Based on Acoustic Measures Using Artificial Neural Networks
Classifying Parkinson's Disease Based on Acoustic Measures Using Artificial Neural Networks
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Classifying Parkinson's Disease Based on Acoustic Measures Using Artificial Neural Networks

Berus, Lucijano ; Klancnik, Simon ; Brezocnik, Miran ; Ficko, Mirko

Sensors (Basel, Switzerland), 2018-12, Vol.19 (1), p.16 [Periódico revisado por pares]

Switzerland: MDPI AG

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6
Automatic calibration of microscopic traffic simulation models using artificial neural networks
Automatic calibration of microscopic traffic simulation models using artificial neural networks
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Automatic calibration of microscopic traffic simulation models using artificial neural networks

Rodrigo França Daguano Leopoldo Rideki Yoshioka 1961-; Marcio Lobo Netto 1962-; Cláudio Luiz Marte 1963-; Cassiano Augusto Isler 1984-; Max Mauro Dias dos Santos; João Francisco Justo Filho 1966-

Sensors Basel v. 23,n. 21, p. 1-23, article nº 8798, Oct. 2023

Basel 2023

Item não circula. Consulte sua biblioteca.(Acessar)

7
Towards interpretable deep learning a feature selection framework for prognostics and health management using deep neural networks
Towards interpretable deep learning a feature selection framework for prognostics and health management using deep neural networks
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Towards interpretable deep learning a feature selection framework for prognostics and health management using deep neural networks

Joaquín Eduardo Figueroa Barraza Enrique López Droguett; Marcelo Ramos Martins 1971-

Sensors Basel v. 21, n. 17, p. 1-30, 2021

Basel 2021

Item não circula. Consulte sua biblioteca.(Acessar)

8
3D Convolutional Neural Networks Initialized from Pretrained 2D Convolutional Neural Networks for Classification of Industrial Parts
3D Convolutional Neural Networks Initialized from Pretrained 2D Convolutional Neural Networks for Classification of Industrial Parts
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3D Convolutional Neural Networks Initialized from Pretrained 2D Convolutional Neural Networks for Classification of Industrial Parts

Merino, Ibon ; Azpiazu, Jon ; Remazeilles, Anthony ; Sierra, Basilio

Sensors (Basel, Switzerland), 2021-02, Vol.21 (4), p.1078 [Periódico revisado por pares]

Switzerland: MDPI

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9
Application of Graph Convolutional Neural Networks Combined with Single-Model Decision-Making Fusion Neural Networks in Structural Damage Recognition
Application of Graph Convolutional Neural Networks Combined with Single-Model Decision-Making Fusion Neural Networks in Structural Damage Recognition
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Application of Graph Convolutional Neural Networks Combined with Single-Model Decision-Making Fusion Neural Networks in Structural Damage Recognition

Li, Xiaofei ; Xu, Langxing ; Guo, Hainan ; Yang, Lu

Sensors (Basel, Switzerland), 2023-11, Vol.23 (23), p.9327 [Periódico revisado por pares]

Switzerland: MDPI AG

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10
Hyperspectral Imaging for the Detection of Glioblastoma Tumor Cells in H&E Slides Using Convolutional Neural Networks
Hyperspectral Imaging for the Detection of Glioblastoma Tumor Cells in H&E Slides Using Convolutional Neural Networks
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Hyperspectral Imaging for the Detection of Glioblastoma Tumor Cells in H&E Slides Using Convolutional Neural Networks

Ortega, Samuel ; Halicek, Martin ; Fabelo, Himar ; Camacho, Rafael ; Plaza, María de la Luz ; Godtliebsen, Fred ; M Callicó, Gustavo ; Fei, Baowei

Sensors (Basel, Switzerland), 2020-03, Vol.20 (7), p.1911 [Periódico revisado por pares]

Switzerland: MDPI AG

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Deste Autor:

  1. Santos, J
  2. Lima, J
  3. Koste, E
  4. Nonato, L
  5. Silva, J

Neste Assunto:

  1. Technology
  2. Engineering
  3. Instruments & Instrumentation
  4. Chemistry
  5. Chemistry, Analytical

  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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