• UCO physical rehabilitation: new dataset and study of human pose estimation methods on physical rehabilitation exercises 

  Aguilar-Ortega, Rafael; Berrral-Soler, Rafael; Jiménez-Velasco, Isabel; Romero Ramírez, Francisco J.; García-Marín, Manuel; Zafra-Palma, Jorge; Muñoz-Salinas, Rafael; Medina-Carnicer, R.; Marín-Jiménez, M.J. (MDPI, 2023)

  Physical rehabilitation plays a crucial role in restoring motor function following injuries or surgeries. However, the challenge of overcrowded waiting lists often hampers doctors’ ability to monitor patients’ recovery ...

• Improving spiking neural network performance with auxiliary learning 

  Cachi, Paolo G.; Ventura Soto, S.; Cios, Krzysztof (MDPI, 2023)

  The use of back propagation through the time learning rule enabled the supervised training of deep spiking neural networks to process temporal neuromorphic data. However, their performance is still below non-spiking neural ...

• On the concept of infinitesimal position vector fields in Galilean spacetimes 

  Caballero, Magdalena; Fuente, Daniel de la; Pelegrín, José A. S.; Rubio, Rafael M. (World Scientific, 2022)

  We introduce two different ways to establish the concept of infinitesimal position vector field between “infinitesimally nearby” observers in a Galilean spacetime as well as show their mathematical equivalence. We also use ...

• ML-k’sNN: Label Dependent k Values for Multi-Label k-Nearest Neighbor Rule 

  Cuevas-Muñoz, José Manuel; García Pedrajas, Nicolás (MDPI, 2023)

  Multi-label classification as a data mining task has recently attracted increasing interest from researchers. Many current data mining applications address problems with instances that belong to more than one category. ...

• sSLAM: Speeded-Up Visual SLAM Mixing Artificial Markers and Temporary Keypoints 

  Romero Ramírez, Francisco J.; Muñoz-Salinas, Rafael; Marín-Jiménez, M.J.; Cazorla, Miguel; Medina-Carnicer, R.; Romero Ramírez, Francisco J. (MDPI, 2023)

  Environment landmarks are generally employed by visual SLAM (vSLAM) methods in the form of keypoints. However, these landmarks are unstable over time because they belong to areas that tend to change, e.g., shadows or moving ...

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