Human Activity Recognition (HAR) has become one of the leading research topics of the last
decade. As sensing technologies have matured and their economic costs have declined, a …

This chapter provides an all-round picture of the development and advances in the fields of
evolving fuzzy systems (EFS) and evolving neuro-fuzzy systems (ENFS) which have been …

Evolving classifiers and especially evolving fuzzy classifiers have been established as a
prominent technique for addressing the recent demands in building classifiers in an …

Evolving classifiers and especially evolving fuzzy classifiers have been established as a
prominent technique for addressing the recent demands in building classifiers in an …

Improving performance of SELFI with smart and explainable detection of retraining at run time
Page 1 Improving performance of SELFI with smart and explainable detection of retraining at …

Time series data is ubiquitous across various domains, including manufacturing, finance,
and healthcare. High-quality annotations are essential for effectively understanding time …

This contribution evaluates semi-automated annotation for generating high-quality data for
multi-channel time series Human Activity Recognition. For this purpose, time series data that …

Researchers face the challenge of defining subject selection criteria when training
algorithms for human activity recognition tasks. The ongoing uncertainty revolves around …

Poor adherence to prescribed drug treatments is one of the leading causes of illness and
treatment failure, which increases re-hospitalizations. In Mexico, the factors that most …

Developing machine learning-based emotion inference models requires numerous ground
truth labels, typically collected through self-reports, which can be burdensome and induce …