An Adaptive Cognitive Model to Integrate Machine Learning and Visual Streaming Data

  1. Esteban García-Cuesta 1
  2. López-López, Jose M. 1
  3. Daniel Gómez-Vergel 1
  4. Javier Huertas-Tato 1
  1. 1 Universidad Europea de Madrid
    info

    Universidad Europea de Madrid

    Madrid, España

    ROR https://ror.org/04dp46240

Libro:
15th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2020): Burgos, Spain ; September 2020
  1. Álvaro Herrero (coord.)
  2. Carlos Cambra (coord.)
  3. Daniel Urda (coord.)
  4. Javier Sedano (coord.)
  5. Héctor Quintián (coord.)
  6. Emilio Corchado (coord.)

Editorial: Springer Suiza

ISBN: 978-3-030-57801-5,  978-3-030-57802-2

Año de publicación: 2021

Páginas: 176-185

Congreso: International Conference on Soft Computing Models in Industrial and Environmental Applications SOCO (15. 2020. Burgos)

Tipo: Aportación congreso

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Resumen

In this paper, we present our currentwork towards developing a context aware visual system with capabilities to generate knowledge using an adaptive cognitive model. Our goal is to assist people in their daily routines using the acquired knowledge in combinationwith a set of machine learning tools to provide prediction and individual routine understanding. This is useful in applications such as assistance to individuals with Alzheimer by helping them to maintain a daily routine based on historical data. The proposed cognitive model is based on simple exponential smoothing technique and provides real time detection of objects and basic relations in the scene. To fulfill these objectives we propose the integration of machine learning tools and memory based knowledge representation.

Fuente de los datos: Dialnet