Browsing Institute of New Imaging Technologies (INIT) by Keyword "machine learning"

Now showing items 1-16 of 16

    • openAccess   A Generative Method for Indoor Localization Using Wi-Fi Fingerprinting 

      Belmonte-Fernández, Óscar; Sansano-Sansano, Emilio; Caballer Miedes, Antonio; Montoliu Colás, Raul; García-Vidal, Rubén; Gascó Compte, Arturo MDPI (2021-03-30)
      Indoor localization is an enabling technology for pervasive and mobile computing applications. Although different technologies have been proposed for indoor localization, Wi-Fi fingerprinting is one of the most used ...

    • openAccess   A set of deep learning algorithms for air quality prediction applications 

      Iskandaryan, Ditsuhi; Ramos, Francisco; Trilles, Sergio Elsevier (2023)
      This paper presents a set of machine learning algorithms, including grid-based (Bidirectional Convolutional Long Short-Term Memory) and graph-based (Attention Temporal Graph Convolutional Network) algorithms to predict air ...

    • openAccess   Air Quality Prediction in Smart Cities Using Machine Learning Technologies Based on Sensor Data: A Review 

      Iskandaryan, Ditsuhi; Ramos, Jose Francisco; Trilles, Sergio MDPI (2020-04-01)
      The influence of machine learning technologies is rapidly increasing and penetrating almost in every field, and air pollution prediction is not being excluded from those fields. This paper covers the revision of the studies ...

    • openAccess   Bidirectional convolutional LSTM for the prediction of nitrogen dioxide in the city of Madrid 

      Iskandaryan, Ditsuhi; Ramos, Jose Francisco; Trilles, Sergio PLoS (2022-06-01)
      Nitrogen dioxide is one of the pollutants with the most significant health effects. Advanced information on its concentration in the air can help to monitor and control further consequences more effectively, while also ...

    • openAccess   Characterising Players of a Cube Puzzle Game with a Two-level Bag of Words 

      Anadón, Xavier; Sanahuja, Pablo; Traver, V. Javier; Lopez, Angeles; Ribelles, Jose Association for Computing Machinery (ACM) (2021-06)
      This work explores an unsupervised approach for modelling players of a 2D cube puzzle game with the ultimate goal of customising the game for particular players based solely on their interaction data. To that end, user ...

    • openAccess   Comparison of Nitrogen Dioxide Predictions During a Pandemic and Non-pandemic Scenario in the City of Madrid using a Convolutional LSTM Network 

      Iskandaryan, Ditsuhi; Ramos, Jose Francisco; Trilles, Sergio World Scientific (2022-06-22)
      Traditionally, machine learning technologies with the methods and capabilities available, combined with a geospatial dimension, can perform predictive analyzes of air quality with greater accuracy. However, air pollution ...

    • openAccess   Ensembling Multiple Radio Maps with Dynamic Noise in Fingerprint-based Indoor Positioning 

      Torres-Sospedra, Joaquín; Aranda Polo, Fernando Jesús; Álvarez, Fernando J.; Quezada Gaibor, Darwin; Silva, Ivo; Pendão, Cristiano; Moreira, Adriano Institute of Electrical and Electronics Engineers (2021-06-15)
      Fingerprint-based indoor positioning is widely used in many contexts, including pedestrian and autonomous vehicles navigation. Many approaches have used traditional Machine Learning models to deal with fingerprinting, ...

    • openAccess   Features Exploration from Datasets Vision in Air Quality Prediction Domain 

      Iskandaryan, Ditsuhi; Ramos, Jose Francisco; Trilles, Sergio MDPI (2021-02-28)
      Air pollution and its consequences are negatively impacting on the world population and the environment, which converts the monitoring and forecasting air quality techniques as essential tools to combat this problem. To ...

    • openAccess   Integrating Concepts of Artificial Intelligence in the EO4GEO Body of Knowledge 

      Lemmens, Rob; Lang, Stefan; Albrecht, Florian; Augustijn, E.; Granell, Carlos; Olijslagers, Marc; Pathe, C.; Dubois, C.; Stelmaszczuk-Górska, Martyna A. International Society for Photogrammetry and Remote Sensing (2022-06)
      The EO4GEO Body of Knowledge (BoK) forms a structure of concepts and relationships between them, describing the domain of Earth Observation and Geo-Information (EO/GI). Each concept carries a short description, a list of ...

    • openAccess   Intelligent on-demand design of phononic metamaterials 

      Jin, Yabin; He, Liangshu; Wen, Zhihui; Mortazavi, Bohayra; Guo, Hongwei; Torrent, Daniel; Djafari Rouhani, Bahram; Rabczuk, Timon; Zhuang, Xiaoying; Li, Yan De Gruyter (2022-01-04)
      With the growing interest in the field of artificial materials, more advanced and sophisticated functionalities are required from phononic crystals and acoustic metamaterials. This implies a high computational effort and ...

    • openAccess   Machine learning assisted intelligent design of meta structures: a review 

      He, Liangshu; Li, Yan; Torrent, Daniel; Zhuang, Xiaoying; Rabczuk, Timon; Jin, Yabin OAE Publishing (2023-10)
      In recent years, the rapid development of machine learning (ML) based on data-driven or environment interaction has injected new vitality into the field of meta-structure design. As a supplement to the traditional ...

    • openAccess   Resample-smoothing of Voronoi intensity estimators 

      Moradi, Mehdi; Cronie, Ottmar; Rubak, Ege; Lachieze-Rey, Raphael; Mateu, Jorge Springer (2019)
      Voronoi estimators are non-parametric and adaptive estimators of the intensity of a point process. The intensity estimateat a given location is equal to the reciprocal of the size of the Voronoi/Dirichlet cell containing ...

    • openAccess   The Effect of Weather in Soccer Results: An Approach Using Machine Learning Techniques 

      Iskandaryan, Ditsuhi; Ramos, Jose Francisco; Palinggi, Denny Asarias; Trilles, Sergio MDPI (2020-09-26)
      The growing popularity of soccer has led to the prediction of match results becoming of interest to the research community. The aim of this research is to detect the effects of weather on the result of matches by implementing ...

    • openAccess   The Use of Machine Learning Techniques for Optimal Multicasting in 5G NR Systems 

      Chukhno, Nadezhda; Chukhno, Olga; Moltchanov, Dmitri; Gaydamaka, Anna; Samuylov, Andrey; Molinaro, Antonella; Koucheryavy, Yevgeni; IERA, Antonio; ARANITI, Giuseppe IEEE (2022-09-28)
      Multicasting is a key feature of cellular systems, which provides an efficient way to simultaneously disseminate a large amount of traffic to multiple subscribers. However, the efficient use of multicast services in ...

    • closedAccess   Towards Accelerated Localization Performance Across Indoor Positioning Datasets 

      Klus, Lucie; Quezada Gaibor, Darwin; Torres-Sospedra, Joaquín; Lohan, Elena Simona; Granell, Carlos; Nurmi, Jari IEEE (2022)
      The localization speed and accuracy in the indoor scenario can greatly impact the Quality of Experience of the user. While many individual machine learning models can achieve comparable positioning performance, their ...

    • openAccess   Transfer Learning for Convolutional Indoor Positioning Systems 

      Klus, Roman; Klus, Lucie; Talvitie, Jukka; Pihlajasalo, Jaakko; Torres-Sospedra, Joaquín; Valkama, Mikko IEEE (2021-11-29)
      Fingerprinting is a widely used technique in indoor positioning, mainly due to its simplicity. Usually, this technique is used with the deterministic k - Nearest Neighbors (k-NN) algorithm. Utilizing a neural network model ...