Application of Pattern Recognition and Machine Learning

Special Issue Editors


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Guest Editor
Department of Computer Science and Artificial Intelligence, Universidad de Granada, 18014 Granada, Spain
Interests: machine learning; pattern recognition; neural networks; deep learning; metaheuristics algorithms; artificial intelligence; applied artificial intelligence; fuzzy logic; energy consumption modelling; psychology and artificial intelligence
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Software Engineering, University of Granada, 18014 Granada, Spain
Interests: time series; data mining; artificial neural networks; energy efficiency; energy consumption modelling; soil science; unsupervised algorithms
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We can announce a new Special Issue entitled “Application of Pattern Recognition and Machine Learning” in the journal BDCC.

In today’s world, pattern recognition is transforming how we analyse the vast amount of data generated by uncountable sources. On the other hand, machine learning is speeding up that change and bringing new possibilities across many fields. Together, they are becoming essential tools for tackling complex scientific and practical problems.

We can see their effects in many areas. For example, in healthcare, where algorithms help to detect tumours in medical images; in language technologies, where chatbots and summarizers understand and generate text; in psychology, where it is possible to predict an individual’s personality through tweets or predict the estimation of psychological variables; in soil science, where they identify soil types and detect spatial patterns from observations; in autonomous systems, where perception and control are used in vehicles; in environmental monitoring, where models predict air quality and spot emerging issues; and in energy, where forecasting and fault detection help to keep grids running efficiently.

Motivated by these few examples, this Special Issue will collect novel research and real-world implementations that push pattern recognition and machine learning forward. We are looking for new algorithms, improved models and practical solutions that show innovation. Submissions can cover theory, experiments or applied work, especially when they demonstrate real impact.

We invite original research articles and critical reviews on topics related (but not limited) to the following:

  • Deep learning for images, speech and text;
  • Few-shot, zero-shot and transfer learning;
  • Anomaly and outlier detection in complex systems;
  • Time-series and sequential pattern analysis;
  • Data fusion and cross-modal learning;
  • Graph deep learning;
  • Federated learning;
  • Interpretive knowledge discovery;
  • Systems analytics;
  • Forecasting and fault detection;
  • Artificial neural networks.

Prof. Dr. María del Carmen Pegalajar Jiménez
Dr. Luis G. Baca Ruiz
Guest Editors

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Keywords

  • pattern recognition
  • machine learning
  • deep learning
  • self‑supervised learning
  • explainability
  • interpretability
  • few‑shot learning
  • transfer learning
  • anomaly detection
  • time‑series analysis
  • multimodal fusion
  • graph learning
  • federated learning
  • artificial neural networks
  • analytics

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Published Papers

This special issue is now open for submission.
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