loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Yuriy V. Shkvarko ; Juan I. Yañez and Gustavo D. Martín del Campo

Affiliation: CINVESTAV-IPN, Mexico

Keyword(s): Harsh sensing environment, neural network, regularization, sensor/method fusion.

Abstract: We address a novel neural network computing-based approach to the problem of near real-time feature enhanced fusion of remote sensing (RS) imagery acquired in harsh sensing environments. The novel proposition consists in adapting the Hopfield-type maximum entropy neural network (MENN) computational framework to solving the RS image fusion inverse problem. The feature enhanced fusion is performed via aggregating the descriptive experiment design with the variational analysis (VA) inspired regularization frameworks that lead to an adaptive procedure for proper adjustments of the MENN synaptic weights and bias inputs. We feature on the considerably speeded-up implementation of the MENN-based RS image fusion and verify the overall image enhancement efficiency via computer simulations with real-world RS imagery.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 44.202.183.118

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Shkvarko, Y.; Yañez, J. and Martín del Campo, G. (2014). A Novel Neural Network Computing Based Way to Sensor and Method Fusion in Harsh Operational Environments. In Proceedings of the International Workshop on Artificial Neural Networks and Intelligent Information Processing (ICINCO 2014) - ANNIIP; ISBN 978-989-758-041-3, SciTePress, pages 19-26. DOI: 10.5220/0005125100190026

@conference{anniip14,
author={Yuriy V. Shkvarko. and Juan I. Yañez. and Gustavo D. {Martín del Campo}.},
title={A Novel Neural Network Computing Based Way to Sensor and Method Fusion in Harsh Operational Environments},
booktitle={Proceedings of the International Workshop on Artificial Neural Networks and Intelligent Information Processing (ICINCO 2014) - ANNIIP},
year={2014},
pages={19-26},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005125100190026},
isbn={978-989-758-041-3},
}

TY - CONF

JO - Proceedings of the International Workshop on Artificial Neural Networks and Intelligent Information Processing (ICINCO 2014) - ANNIIP
TI - A Novel Neural Network Computing Based Way to Sensor and Method Fusion in Harsh Operational Environments
SN - 978-989-758-041-3
AU - Shkvarko, Y.
AU - Yañez, J.
AU - Martín del Campo, G.
PY - 2014
SP - 19
EP - 26
DO - 10.5220/0005125100190026
PB - SciTePress