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José M. Moya

3 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author3

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.DC1
  • cs.NI1
  • q-bio.QM1
ORCID 0000-0001-7926-9384

identity via Semantic Scholar / OpenAlex

most citedToward Ultra-Low-Power Remote Health Monitoring: An Optimal and Adaptive Compressed Sensing Framework for Activity Recognition

51 citations · 78 across the 3 of their papers we have counts for

collaborators

3 papers

cs.DC2024★ 12 cited

Enhancing Regression Models for Complex Systems Using Evolutionary Techniques for Feature Engineering

Patricia Arroba, José L. Risco-Martín, Marina Zapater +2

This work proposes an automatic methodology for modeling complex systems. Our methodology is based on the combination of Grammatical Evolution and classical regression to obtain an…

q-bio.QM2024★ 15 cited

Modeling methodology for the accurate and prompt prediction of symptomatic events in chronic diseases

Josué Pagán, José L. Risco-Martín, José M. Moya +1

Prediction of symptomatic crises in chronic diseases allows to take decisions before the symptoms occur, such as the intake of drugs to avoid the symptoms or the activation of medi…

cs.NI2023★ 51 cited

Toward Ultra-Low-Power Remote Health Monitoring: An Optimal and Adaptive Compressed Sensing Framework for Activity Recognition

J. Pagan, R. Fallahzadeh, M. Pedram +4

Activity recognition, as an important component of behavioral monitoring and intervention, has attracted enormous attention, especially in Mobile Cloud Computing (MCC) and Remote H…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.