Publicaciones en las que colabora con Chris Nugent (33)

2020

  1. Evaluation of convolutional neural networks for the classification of falls from heterogeneous thermal vision sensors

    International Journal of Distributed Sensor Networks, Vol. 16, Núm. 5

  2. Fuzzy cloud-fog computing approach application for human activity recognition in smart homes

    Journal of Intelligent and Fuzzy Systems, Vol. 38, Núm. 1, pp. 709-721

2019

  1. Straightforward Recognition of Daily Objects in Smart Environments from Wearable Vision Sensor

    2019 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2019

2018

  1. Collection of a Diverse, Realistic and Annotated Dataset for Wearable Activity Recognition

    2018 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2018

  2. Ensemble classifier of long short-term memory with fuzzy temporal windows on binary sensors for activity recognition

    Expert Systems with Applications, Vol. 114, pp. 441-453

  3. The experience of developing the UJAmI Smart Lab

    IEEE Access, Vol. 6, pp. 34631-34642

2017

  1. Comparison of fiducial marker detection and object interaction in activities of daily living utilising a wearable vision sensor

    International Journal of Communication Systems

  2. Computational Intelligence for Smart Environments

    International Journal of Computational Intelligence Systems, Vol. 10, Núm. 1, pp. 1250-1251

  3. Fuzzy fog computing: A linguistic approach for knowledge inference in wearable devices

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  4. Indoor localisation through object detection within multiple environments utilising a single wearable camera

    Health and Technology, Vol. 7, Núm. 1, pp. 51-60

  5. Optimizing the configuration of an heterogeneous architecture of sensors for activity recognition, using the extended belief rule-based inference methodology

    Microprocessors and Microsystems, Vol. 52, pp. 381-390