Zobrazeno 1 - 10 of 52 pro vyhledávání: '"José Valente de Oliveira"'
1
Akademický článek
Embedding a Real-Time Strawberry Detection Model into a Pesticide-Spraying Mobile Robot for Greenhouse Operation
Autor: Khalid El Amraoui, Mohamed El Ansari, Mouataz Lghoul, Mustapha El Alaoui, Abdelkrim Abanay, Bouazza Jabri, Lhoussaine Masmoudi, José Valente de Oliveira
Publikováno v: Applied Sciences, Vol 14, Iss 16, p 7195 (2024)
The real-time detection of fruits and plants is a crucial aspect of digital agriculture, enhancing farming efficiency and productivity. This study addresses the challenge of embedding a real-time strawberry detection system in a small mobile robot op
Externí odkaz: https://doaj.org/article/d36e69bbf5904e0d95936c184272e091
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2
Akademický článek
Exploiting Generative Adversarial Networks as an Oversampling Method for Fault Diagnosis of an Industrial Robotic Manipulator
Autor: Ziqiang Pu, Diego Cabrera, René-Vinicio Sánchez, Mariela Cerrada, Chuan Li, José Valente de Oliveira
Publikováno v: Applied Sciences, Vol 10, Iss 21, p 7712 (2020)
Data-driven machine learning techniques play an important role in fault diagnosis, safety, and maintenance of the industrial robotic manipulator. However, these methods require data that, more often that not, are hard to obtain, especially data colle
Externí odkaz: https://doaj.org/article/7e964dc3684447b9a261c20ef988a179
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3
Sliced Wasserstein cycle consistency generative adversarial networks for fault data augmentation of an industrial robot
Autor: Ziqiang Pu, Diego Cabrera, Chuan Li, José Valente de Oliveira
We investigate the role of the loss function in cycle consistency generative adversarial networks (CycleGANs). Namely, the sliced Wasserstein distance is proposed for this type of generative model. Both the unconditional and the conditional CycleGANs
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::768af7f98075c7c5b0449d5b3bb45a06
https://hdl.handle.net/10400.1/19480
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4
One-Shot Fault Diagnosis of Three-Dimensional Printers Through Improved Feature Space Learning
Autor: José Valente de Oliveira, Mariela Cerrada, Diego Cabrera, Chuan Li, Fernando Sancho, René-Vinicio Sánchez
Publikováno v: IEEE Transactions on Industrial Electronics. 68:8768-8776
Signal acquisition from mechanical systems working in faulty conditions is normally expensive. As a consequence, supervised learning-based approaches are hardly applicable. To address this problem, a one-shot learning-based approach is proposed for m
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::25dce6820bdc9e8829d6363e36e72e38
https://doi.org/10.1109/tie.2020.3013546
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5
A Systematic Review of Fuzzy Formalisms for Bearing Fault Diagnosis
Autor: Grover Zurita, Mariela Cerrada, José Valente de Oliveira, René-Vinicio Sánchez, Chuan Li, Diego Cabrera
Publikováno v: IEEE Transactions on Fuzzy Systems. 27:1362-1382
Bearings are fundamental mechanical components in rotary machines (engines, gearboxes, generators, radars, turbines, etc.) that have been identified as one of the primary causes of failure in these machines. This makes bearing fault diagnosis (detect
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::7bdc21038053332d0044f6bd564ecc93
https://doi.org/10.1109/tfuzz.2018.2878200
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6
Fusing convolutional generative adversarial encoders for 3D printer fault detection with only normal condition signals
Autor: Mariela Cerrada, Jianyu Long, René-Vinicio Sánchez, Diego Cabrera, Chuan Li, Fernando Sancho, José Valente de Oliveira
Publikováno v: Repositório Científico de Acesso Aberto de Portugal
Repositório Científico de Acesso Aberto de Portugal (RCAAP)
instacron:RCAAP
idUS: Depósito de Investigación de la Universidad de Sevilla
Universidad de Sevilla (US)
idUS. Depósito de Investigación de la Universidad de Sevilla
instname
Collecting data from mechanical systems in abnormal conditions is expensive and time consuming. Consequently, fault detection approaches based on classical supervised learning working with both normal and abnormal data are not applicable in some cond
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::54d71ba510a271d9d3b2fd31eefa12c2
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7
Exploiting Generative Adversarial Networks as an Oversampling Method for Fault Diagnosis of an Industrial Robotic Manipulator
Autor: Chuan Li, Mariela Cerrada, Ziqiang Pu, Diego Cabrera, José Valente de Oliveira, René-Vinicio Sánchez
Publikováno v: Applied Sciences
Volume 10
Issue 21
Applied Sciences, Vol 10, Iss 7712, p 7712 (2020)
Repositório Científico de Acesso Aberto de Portugal
Repositório Científico de Acesso Aberto de Portugal (RCAAP)
instacron:RCAAP
Data-driven machine learning techniques play an important role in fault diagnosis, safety, and maintenance of the industrial robotic manipulator. However, these methods require data that, more often that not, are hard to obtain, especially data colle
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::db4382be1ef890ba6ca6fc675e3123c6
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8
Automatic acoustic target detection and classification off the Coast of Portugal
Autor: Sergio M. Jesus, José Valente de Oliveira, Razi Sabara, C. Soares, Florian Zabel
Ocean noise has been a topic of research for many years, for its impact in sonar detection, underwater communications and ocean acoustic observation in general. Recently, ocean sound has been designated as an Essential Ocean Variable (EOV) and is the
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1501f34e93ef78d4df90b80257f87b93
https://hdl.handle.net/10400.1/17139
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