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Refinado por: Nome da Publicação: Sensors remover
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Machine Learning Models for Slope Stability Classification of Circular Mode Failure: An Updated Database and Automated Machine Learning (AutoML) Approach
Machine Learning Models for Slope Stability Classification of Circular Mode Failure: An Updated Database and Automated Machine Learning (AutoML) Approach
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Machine Learning Models for Slope Stability Classification of Circular Mode Failure: An Updated Database and Automated Machine Learning (AutoML) Approach

Ma, Junwei ; Jiang, Sheng ; Liu, Zhiyang ; Ren, Zhiyuan ; Lei, Dongze ; Tan, Chunhai ; Guo, Haixiang

Sensors (Basel, Switzerland), 2022-11, Vol.22 (23), p.9166 [Periódico revisado por pares]

Switzerland: MDPI AG

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2
Machine learning for the detection and diagnosis of anomalies in applications driven by electric motors
Machine learning for the detection and diagnosis of anomalies in applications driven by electric motors
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Machine learning for the detection and diagnosis of anomalies in applications driven by electric motors

Fábio Ferraz Júnior Roseli Aparecida Francelin Romero; Sheng-Jen Hsieh

Sensors Basel v. 23, n. 24, p. 1-25, 2023

Basel 2023

Localização: ICMC - Inst. Ciên. Mat. Computação    (PROD-3172974 )(Acessar)

3
A Machine Learning Approach to Diagnosing Lung and Colon Cancer Using a Deep Learning-Based Classification Framework
A Machine Learning Approach to Diagnosing Lung and Colon Cancer Using a Deep Learning-Based Classification Framework
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A Machine Learning Approach to Diagnosing Lung and Colon Cancer Using a Deep Learning-Based Classification Framework

Masud, Mehedi ; Sikder, Niloy ; Nahid, Abdullah-Al ; Bairagi, Anupam Kumar ; AlZain, Mohammed A

Sensors (Basel, Switzerland), 2021-01, Vol.21 (3), p.748 [Periódico revisado por pares]

Switzerland: MDPI AG

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4
Chemical Gas Sensors: Recent Developments, Challenges, and the Potential of Machine Learning-A Review
Chemical Gas Sensors: Recent Developments, Challenges, and the Potential of Machine Learning-A Review
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Chemical Gas Sensors: Recent Developments, Challenges, and the Potential of Machine Learning-A Review

Yaqoob, Usman ; Younis, Mohammad I

Sensors (Basel, Switzerland), 2021-04, Vol.21 (8), p.2877 [Periódico revisado por pares]

Switzerland: MDPI AG

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5
An Overview of Machine Learning within Embedded and Mobile Devices–Optimizations and Applications
An Overview of Machine Learning within Embedded and Mobile Devices–Optimizations and Applications
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An Overview of Machine Learning within Embedded and Mobile Devices–Optimizations and Applications

Ajani, Taiwo Samuel ; Imoize, Agbotiname Lucky ; Atayero, Aderemi A.

Sensors (Basel, Switzerland), 2021-06, Vol.21 (13), p.4412 [Periódico revisado por pares]

MDPI

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6
Ferroelectret-based hydrophone employed in oil identification - a machine learning approach
Ferroelectret-based hydrophone employed in oil identification - a machine learning approach
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Ferroelectret-based hydrophone employed in oil identification - a machine learning approach

Daniel R. de Luna T. T. C Palitó; Y. A. O Assagra; R. A. P Altafim; J. P Carmo; R. A. C Altafim; Antonio Adilton Oliveira Carneiro; Vicente A. de Sousa Junior

Sensors Basel v. 20, n. 10, art. 2979, p. 1-18, 2020

Basel 2020

Localização: FFCLRP - Fac. Fil. Ciên. Let. de R. Preto    (pcd 3077169 Acervo Digital )(Acessar)

7
Ferroelectret-based hydrophone employed in oil identification a machine learning approach
Ferroelectret-based hydrophone employed in oil identification a machine learning approach
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Ferroelectret-based hydrophone employed in oil identification a machine learning approach

Daniel R. de Luna Thamyres Tâmulla Cavalcante Palitó; Yuri Andrey Olivato Assagra; Ruy Alberto Pisani Altafim; João Paulo Pereira do Carmo; Ruy Alberto Corrêa Altafim; Adilton Carneiro; Vicente Angelo de Sousa Junior

Sensors Basel, Switzerland : MDPI, 2020 v. 20, n. 10, article 2979, p. 1-18, 2020

Basel, Switzerland 2020

Localização: EESC - Esc. Engenharia de São Carlos    (PROD-022502 )(Acessar)

8
Tackling Faults in the Industry 4.0 Era-A Survey of Machine-Learning Solutions and Key Aspects
Tackling Faults in the Industry 4.0 Era-A Survey of Machine-Learning Solutions and Key Aspects
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Tackling Faults in the Industry 4.0 Era-A Survey of Machine-Learning Solutions and Key Aspects

Angelopoulos, Angelos ; Michailidis, Emmanouel T ; Nomikos, Nikolaos ; Trakadas, Panagiotis ; Hatziefremidis, Antonis ; Voliotis, Stamatis ; Zahariadis, Theodore

Sensors (Basel, Switzerland), 2019-12, Vol.20 (1), p.109 [Periódico revisado por pares]

Switzerland: MDPI AG

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9
Identification of Risk Factors Associated with Obesity and Overweight-A Machine Learning Overview
Identification of Risk Factors Associated with Obesity and Overweight-A Machine Learning Overview
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Identification of Risk Factors Associated with Obesity and Overweight-A Machine Learning Overview

Chatterjee, Ayan ; Gerdes, Martin W ; Martinez, Santiago G

Sensors (Basel, Switzerland), 2020-05, Vol.20 (9), p.2734 [Periódico revisado por pares]

Switzerland: MDPI

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10
Prediction of Freezing of Gait in Parkinson's Disease Using Wearables and Machine Learning
Prediction of Freezing of Gait in Parkinson's Disease Using Wearables and Machine Learning
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Prediction of Freezing of Gait in Parkinson's Disease Using Wearables and Machine Learning

Borzì, Luigi ; Mazzetta, Ivan ; Zampogna, Alessandro ; Suppa, Antonio ; Olmo, Gabriella ; Irrera, Fernanda

Sensors (Basel, Switzerland), 2021-01, Vol.21 (2), p.614 [Periódico revisado por pares]

Switzerland: MDPI AG

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Deste Autor:

  1. Assagra, Y
  2. Romero, R
  3. Palitó, T
  4. Luna, D
  5. Sousa Junior, V

Neste Assunto:

  1. Technology
  2. Engineering
  3. Chemistry
  4. Instruments & Instrumentation
  5. Physical Sciences

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

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