DOAJ Open Access 2022

Recreating Lunar Environments by Fusion of Multimodal Data Using Machine Learning Models

Ana C. Castillo Jesus A. Marroquin-Escobedo Santiago Gonzalez-Irigoyen Marlene Martinez-Santoyo Rafaela Villalpando-Hernandez +1 lainnya

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Abstrak

The latest satellite infrastructure for data processing, transmission and reception can certainly be improved by upgrading tools used to deal with very large amounts of data from every different sensor incorporated within the space missions. In order to develop a better technique to process data, in this paper we will take an insight into multimodal data fusion using machine learning algorithms. This paper discusses how machine learning models are used to recreate environments from heterogeneous, multi-modal data sets. In particular, for those models based on neural networks, the most important difficulty is the vast number of training objects of the connected neural network based on Convolutional Neural Networks (CNN) to avoid overfitting and underfitting of the models.

Topik & Kata Kunci

Engineering machinery, tools, and implements

Penulis (6)

Ana C. Castillo

Jesus A. Marroquin-Escobedo

Santiago Gonzalez-Irigoyen

Marlene Martinez-Santoyo

Rafaela Villalpando-Hernandez

Cesar Vargas-Rosales

Format Sitasi

APA MLA BibTeX

Castillo, A.C., Marroquin-Escobedo, J.A., Gonzalez-Irigoyen, S., Martinez-Santoyo, M., Villalpando-Hernandez, R., Vargas-Rosales, C. (2022). Recreating Lunar Environments by Fusion of Multimodal Data Using Machine Learning Models. https://doi.org/10.3390/ecsa-9-13326

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Informasi Jurnal

Tahun Terbit: 2022
Sumber Database: DOAJ
DOI: 10.3390/ecsa-9-13326
Akses: Open Access ✓