An Adaptive Cognitive Model to Integrate Machine Learning and Visual Streaming Data
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Esteban García-Cuesta [1] ; López-López, Jose M. [1] ; Daniel Gómez-Vergel [1] ; Javier Huertas-Tato [1]
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[1] Universidad Europea de Madrid
Universidad Europea de Madrid
Madrid, España
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- Localización: 15th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2020): Burgos, Spain ; September 2020 / coord. por Álvaro Herrero Cosío, Carlos Cambra Baseca, Daniel Urda Muñoz, Javier Sedano Franco, Héctor Quintián Pardo, Emilio Santiago Corchado Rodríguez, 2021, ISBN 978-3-030-57802-2, págs. 176-185
- Idioma: inglés
- Texto completo no disponible (Saber más ...)
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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.
