Ángel Miguel García-Vico

Orcid: 0000-0003-1583-2128

According to our database1, Ángel Miguel García-Vico authored at least 26 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Combining traditional and spiking neural networks for energy-efficient detection of Eimeria parasites.
Appl. Soft Comput., 2024

Low Consumption Models for Disease Diagnosis in Isolated Farms.
Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2024, 2024

Deep Learning Inference on Edge: A Preliminary Device Comparison.
Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2024, 2024

Advancing Computational Frontiers: Spiking Neural Networks in High-Energy Efficiency Computing Across Diverse Domains.
Proceedings of the Advances in Artificial Intelligence, 2024

2023
A Multiclustering Evolutionary Hyperrectangle-Based Algorithm.
Int. J. Comput. Intell. Syst., December, 2023

Clustering: an R library to facilitate the analysis and comparison of cluster algorithms.
Prog. Artif. Intell., March, 2023

A distributed evolutionary fuzzy system-based method for the fusion of descriptive emerging patterns in data streams.
Inf. Fusion, 2023

TSFEDL: A python library for time series spatio-temporal feature extraction and prediction using deep learning.
Neurocomputing, 2023

FAS-CT: FPGA-Based Acceleration System with Continuous Training.
Proceedings of the Communication Papers of the 18th Conference on Computer Science and Intelligence Systems, 2023

2022
TSFEDL: A Python Library for Time Series Spatio-Temporal Feature Extraction and Prediction using Deep Learning (with Appendices on Detailed Network Architectures and Experimental Cases of Study).
CoRR, 2022

Performance/Resources Comparison of Hardware Implementations on Fully Connected Network Inference.
Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2022, 2022

A Case of Study with the Clustering R Library to Measure the Quality of Cluster Algorithms.
Proceedings of the Hybrid Artificial Intelligent Systems - 17th International Conference, 2022

2021
A cellular-based evolutionary approach for the extraction of emerging patterns in massive data streams.
Expert Syst. Appl., 2021

A Comparison of Techniques for Virtual Concept Drift Detection.
Proceedings of the 16th International Conference on Soft Computing Models in Industrial and Environmental Applications, 2021

A Preliminary Analysis on Software Frameworks for the Development of Spiking Neural Networks.
Proceedings of the Hybrid Artificial Intelligent Systems - 16th International Conference, 2021

2020
FEPDS: A Proposal for the Extraction of Fuzzy Emerging Patterns in Data Streams.
IEEE Trans. Fuzzy Syst., 2020

E2PAMEA: A fast evolutionary algorithm for extracting fuzzy emerging patterns in big data environments.
Neurocomputing, 2020

A Preliminary Many Objective Approach for Extracting Fuzzy Emerging Patterns.
Proceedings of the 15th International Conference on Soft Computing Models in Industrial and Environmental Applications, 2020

2019
Subgroup Discovery on Multiple Instance Data.
Int. J. Comput. Intell. Syst., 2019

A Big Data Approach for the Extraction of Fuzzy Emerging Patterns.
Cogn. Comput., 2019

2018
An overview of emerging pattern mining in supervised descriptive rule discovery: taxonomy, empirical study, trends, and prospects.
WIREs Data Mining Knowl. Discov., 2018

MOEA-EFEP: Multi-Objective Evolutionary Algorithm for Extracting Fuzzy Emerging Patterns.
IEEE Trans. Fuzzy Syst., 2018

Improvement of subgroup descriptions in noisy data by detecting exceptions.
Prog. Artif. Intell., 2018

2017
A first approach to handle fuzzy emerging patterns mining on big data problems: The EvAEFP-spark algorithm.
Proceedings of the 2017 IEEE International Conference on Fuzzy Systems, 2017

2016
The influence of noise on the evolutionary fuzzy systems for subgroup discovery.
Soft Comput., 2016

Analysing Concentrating Photovoltaics Technology Through the Use of Emerging Pattern Mining.
Proceedings of the International Joint Conference SOCO'16-CISIS'16-ICEUTE'16, 2016


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