Sergio Moreno-Álvarez

Orcid: 0000-0002-1858-9920

Affiliations:
  • University of Extremadura, Cáceres, Spain


According to our database1, Sergio Moreno-Álvarez authored at least 18 papers between 2019 and 2024.

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

Timeline

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Bibliography

2024
Hashing for Retrieving Long-Tailed Distributed Remote Sensing Images.
IEEE Trans. Geosci. Remote. Sens., 2024

Cloud-Based Analysis of Large-Scale Hyperspectral Imagery for Oil Spill Detection.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2024

2023
Parameter-Free Attention Network for Spectral-Spatial Hyperspectral Image Classification.
IEEE Trans. Geosci. Remote. Sens., 2023

AAtt-CNN: Automatic Attention-Based Convolutional Neural Networks for Hyperspectral Image Classification.
IEEE Trans. Geosci. Remote. Sens., 2023

A Comprehensive Survey of Imbalance Correction Techniques for Hyperspectral Data Classification.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2023

Cloud Implementation of Extreme Learning Machine for Hyperspectral Image Classification.
IEEE Geosci. Remote. Sens. Lett., 2023

2022
Heterogeneous gradient computing optimization for scalable deep neural networks.
J. Supercomput., 2022

Multiple Attention-Guided Capsule Networks for Hyperspectral Image Classification.
IEEE Trans. Geosci. Remote. Sens., 2022

Remote Sensing Image Classification Using CNNs With Balanced Gradient for Distributed Heterogeneous Computing.
IEEE Geosci. Remote. Sens. Lett., 2022

Deep Attention-Driven HSI Scene Classification Based on Inverted Dot-Product.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2022

Optimizing Distributed Deep Learning in Heterogeneous Computing Platforms for Remote Sensing Data Classification.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2022

2021
Deep mixed precision for hyperspectral image classification.
J. Supercomput., 2021

Distributed Deep Learning for Remote Sensing Data Interpretation.
Proc. IEEE, 2021

Heterogeneous model parallelism for deep neural networks.
Neurocomputing, 2021

2020
A tool to assess the communication cost of parallel kernels on heterogeneous platforms.
J. Supercomput., 2020

Training deep neural networks: a static load balancing approach.
J. Supercomput., 2020

Performance evaluation of model-driven partitioning algorithms for data-parallel kernels on heterogeneous platforms.
Comput. Math. Methods, 2020

2019
Analytical Communication Performance Models as a metric in the partitioning of data-parallel kernels on heterogeneous platforms.
J. Supercomput., 2019


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