Angel García Vico
Categoría
DoctorContacto
agvico@ujVnhxUtqHvxaen.es
Organismo
UJA
| Total | Desde 2019: | |
|---|---|---|
| Citas | Total: 295 | Desde 2019: 258 |
| Índice H | Total: 9 | Desde 2019: 9 |
| Índice i10 | Total: 9 | Desde 2019: 8 |
Publicaciones (46)
| Título | Autores | Año |
|---|---|---|
| Combining traditional and spiking neural networks for energy-efficient detection of Eimeria parasites | IX Vázquez, BWD Ayasi, H Seker, J Luengo, J Sedano, AM García-Vico. | 2024 |
| Advancing Computational Frontiers: Spiking Neural Networks in High-Energy Efficiency Computing Across Diverse Domains | B Ayasi, ÁM García-Vico, CJ Carmona, M Saleh. | 2024 |
| Deep Learning Inference on Edge: A Preliminary Device Comparison | ML González, J Ruiz, L Andrés, R Lozada, ES Skibinsky, J Fernández, .... | 2024 |
| Low Consumption Models for Disease Diagnosis in Isolated Farms | IX Vázquez, AM García-Vico, H Seker, J Sedano. | 2024 |
| Optimization of Transport Routes Through a Social Interaction Algorithm-Based Application | DI Valdivia Alcalá, ÁM García Vico, CJ Carmona del Jesús. | 2024 |
| Exploring the implementation of LSTM inference on FPGA | ML González, R Lozada, J Ruiz, ES Skibinsky-Gitlin, ÁM García-Vico, .... | 2023 |
| Consumption–Production Profile Categorization in Energy Communities | W Rozas, R Pastor-Vargas, AM García-Vico, J Carpio. | 2023 |
| A Multiclustering Evolutionary Hyperrectangle-Based Algorithm | LAP Martos, ÁM García-Vico, P González, CJC del Jesus. | 2023 |
| An Evolutionary Fuzzy System for Multiclustering in Data Streaming | LAP Martos, ÁM García-Vico, P González, CJ Carmona. | 2023 |
| FAS-CT: FPGA-Based Acceleration System with Continuous Training | MLG Hernandez, J Ruiz, R Lozada, ESS Gitlin, ÁM García-Vico, J Sedano, .... | 2023 |
| Predicting Course Enrollment with Machine Learning and Neural Networks: A Comparative Study of Algorithms | B Ayasi, M Saleh, ÁM García-Vico, C Carmona. | 2023 |
| TSFEDL: A Python Library for Time Series Spatio-Temporal Feature Extraction and Prediction using Deep Learning (with Appendices on Detailed Network Architectures and … | I Aguilera-Martos, ÁM García-Vico, J Luengo, S Damas, FJ Melero, .... | 2022 |
| A Case of Study with the Clustering R Library to Measure the Quality of Cluster Algorithms | LAP Martos, ÁM García-Vico, P González, CJ Carmona. | 2022 |
| Spiking neural networks based on two-dimensional materials | JB Roldan, D Maldonado, C Aguilera-Pedregosa, E Moreno, F Aguirre, .... | 2022 |
| TSFEDL: A Python Library for Time Series Spatio-Temporal Feature Extraction and Prediction using Deep Learning | I Aguilera-Martos, ÁM García-Vico, J Luengo, S Damas, FJ Melero, .... | 2022 |
| A distributed evolutionary fuzzy system-based method for the fusion of descriptive emerging patterns in data streams | ÁM García-Vico, CJ Carmona, P González, MJ del Jesus. | 2022 |
| Clustering: an R library to facilitate the analysis and comparison of cluster algorithms | LAP Martos, ÁM García-Vico, P González, CJ Carmona. | 2022 |
| Performance/Resources Comparison of Hardware Implementations on Fully Connected Network Inference | R Lozada, J Ruiz, ML González, J Sedano, JR Villar, ÁM García-Vico, .... | 2022 |
| A Preliminary Analysis on Software Frameworks for the Development of Spiking Neural Networks | ÁM García-Vico, F Herrera. | 2021 |
| A cellular-based evolutionary approach for the extraction of emerging patterns in massive data streams | ÁM García-Vico, C Carmona, P González, MJ del Jesus. | 2021 |
| A Comparison of Techniques for Virtual Concept Drift Detection | ML González, J Sedano, ÁM García-Vico, JR Villar. | 2021 |
| E2PAMEA: un algoritmo evolutivo para la extraccion eficiente de patrones emergentes difusos en entornos big data | AM Garcia-Vico, D Elizondo, F Charte, P González, CJ Carmona. | 2021 |
| FEPDS: A Proposal for the Extraction of Fuzzy Emerging Patterns in Data Streams | AMG Vico, C Carmona, P Gonzalez, H Seker, MJ Del Jesus. | 2020 |
| E2PAMEA: A fast evolutionary algorithm for extracting fuzzy emerging patterns in big data environments | AM Garcıa-Vico, F Charte, P González, D Elizondo, CJ Carmona. | 2020 |
| A Preliminary Many Objective Approach for Extracting Fuzzy Emerging Patterns | AM Garcia-Vico, CJ Carmona, P Gonzalez, MJ del Jesus. | 2020 |
| Modelos descriptivos basados en aprendizaje supervisado para el tratamiento de big data y flujos continuos de datos | ÁM García Vico. | 2020 |
| Techniques for Evaluating Clustering Data in R | LA Pérez, AM García Vico, P González, CJ Carmona. | 2020 |
| A Big Data Approach for the Extraction of Fuzzy Emerging Patterns | ÁM García-Vico, P González, CJ Carmona, MJ del Jesus. | 2019 |
| Study on the use of different quality measures within a multi-objective evolutionary algorithm approach for emerging pattern mining in big data environments | ÁM García-Vico, P González, CJ Carmona, MJ del Jesus. | 2019 |
| Subgroup Discovery on Multiple Instance Data | JM Luna, CJ Carmona, AM García-Vico, MJ del Jesus, S Ventura. | 2019 |
| Extracting Emerging Patterns with Change Detection in Time for Data Streams | CJ Carmona, AM Garcia-Vico, P Gonzalez, MJ del Jesus. | 2019 |
| ALGORITMOS EVOLUTIVOS DE MINERÍA DE DATOS DESCRIPTIVA PARA FLUJOS CONTINUOS DE DATOS | ÁM García-Vico. | 2019 |
| An overview of emerging pattern mining in supervised descriptive rule discovery: taxonomy, empirical study, trends, and prospects | AM García‐Vico, CJ Carmona, D Martín, M García‐Borroto, MJ del Jesus. | 2018 |
| Moea-efep: Multi-objective evolutionary algorithm for extracting fuzzy emerging patterns | ÁM García-Vico, CJ Carmona, P González, MJ del Jesus. | 2018 |
| Improvement of subgroup descriptions in noisy data by detecting exceptions | P González, ÁM García-Vico, CJ Carmona, MJ del Jesus. | 2018 |
| MOEA-EFEP: Un algoritmo evolutivo multi-objetivo para la extraccion de patrones emergentes difusos | AM Garcia-Vico, CJ Carmona, P González, MJ del Jesus. | 2018 |
| Una primera aproximación para la extracción de patrones emergentes en flujos continuos de datos | ÁMG Vico, CJC del Jesus, PG García, MJ del Jesús Díaz. | 2018 |
| A first approach to handle fuzzy emerging patterns mining on big data problems: The EvAEFP-spark algorithm | AM García-Vico, P González, MJ del Jesús, CJ Carmona. | 2017 |
| Analysing concentrating photovoltaics technology through the use of emerging pattern mining | AM García-Vico, J Montes, J Aguilera, CJ Carmona, MJ del Jesús. | 2016 |
| The influence of noise on the evolutionary fuzzy systems for subgroup discovery | J Luengo, AM García-Vico, MD Pérez-Godoy, CJ Carmona. | 2016 |
| Análisis descriptivo mediante aprendizaje supervisado basado en patrones emergentes | CJ Carmona, FJ Pulgar-Rubio, AM García-Vico, P González, .... | 2015 |
| Usando Algoritmos de Descubrimiento de Subgrupos en R: El Paquete SDR | ÁM Garcıa, F Charte, P González, CJ Carmona, MJ del Jesus. | 2015 |
| DESARROLLO DE UNA LIBRERÍA DE ALGORITMOS DE EXTRACCIÓN DE REGLAS DESCRIPTIVAS EN RY DE LA INTERFAZ DE USUARIO ASOCIADA. | ÁM García-Vico. | 2015 |
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