Rock Detection in a Mars-Like Environment Using a CNN

Federico Furlán; Elsa Rubio; Humberto Sossa; Víctor Ponce

doi:10.1007/978-3-030-21077-9_14

Rock Detection in a Mars-Like Environment Using a CNN

Federico Furlán, Elsa Rubio, Humberto Sossa, Víctor Ponce

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

19 Scopus citations

Abstract

In this paper we study the problem of rock detection in a Mars-like environment. We propose a convolutional neural network (CNN) to obtain a segmented image. The CNN is a modified version of the U-net architecture with a smaller number of parameters to improve the inference time. The performance of the methodology is proved in a dataset that contains several images of a Mars-like environment, achieving an F-score of 78.5%.

Original language	English
Title of host publication	Pattern Recognition - 11th Mexican Conference, MCPR 2019, Proceedings
Editors	Jesús Ariel Carrasco-Ochoa, José Francisco Martínez-Trinidad, José Arturo Olvera-López, Joaquín Salas
Publisher	Springer Verlag
Pages	149-158
Number of pages	10
ISBN (Print)	9783030210762
DOIs	https://doi.org/10.1007/978-3-030-21077-9_14
State	Published - 1 Jan 2019
Event	11th Mexican Conference on Pattern Recognition, MCPR 2019 - Querétaro, Mexico Duration: 26 Jun 2019 → 29 Jun 2019

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11524 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	11th Mexican Conference on Pattern Recognition, MCPR 2019
Country/Territory	Mexico
City	Querétaro
Period	26/06/19 → 29/06/19

Keywords

Convolutional neural networks
Mars exploration
Rock detection

Access to Document

10.1007/978-3-030-21077-9_14

Cite this

Furlán, F., Rubio, E., Sossa, H., & Ponce, V. (2019). Rock Detection in a Mars-Like Environment Using a CNN. In J. A. Carrasco-Ochoa, J. F. Martínez-Trinidad, J. A. Olvera-López, & J. Salas (Eds.), Pattern Recognition - 11th Mexican Conference, MCPR 2019, Proceedings (pp. 149-158). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11524 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-21077-9_14

Furlán, Federico ; Rubio, Elsa ; Sossa, Humberto et al. / Rock Detection in a Mars-Like Environment Using a CNN. Pattern Recognition - 11th Mexican Conference, MCPR 2019, Proceedings. editor / Jesús Ariel Carrasco-Ochoa ; José Francisco Martínez-Trinidad ; José Arturo Olvera-López ; Joaquín Salas. Springer Verlag, 2019. pp. 149-158 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "In this paper we study the problem of rock detection in a Mars-like environment. We propose a convolutional neural network (CNN) to obtain a segmented image. The CNN is a modified version of the U-net architecture with a smaller number of parameters to improve the inference time. The performance of the methodology is proved in a dataset that contains several images of a Mars-like environment, achieving an F-score of 78.5%.",

keywords = "Convolutional neural networks, Mars exploration, Rock detection",

author = "Federico Furl{\'a}n and Elsa Rubio and Humberto Sossa and V{\'i}ctor Ponce",

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editor = "Carrasco-Ochoa, {Jes{\'u}s Ariel} and Mart{\'i}nez-Trinidad, {Jos{\'e} Francisco} and Olvera-L{\'o}pez, {Jos{\'e} Arturo} and Joaqu{\'i}n Salas",

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Furlán, F, Rubio, E, Sossa, H & Ponce, V 2019, Rock Detection in a Mars-Like Environment Using a CNN. in JA Carrasco-Ochoa, JF Martínez-Trinidad, JA Olvera-López & J Salas (eds), Pattern Recognition - 11th Mexican Conference, MCPR 2019, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11524 LNCS, Springer Verlag, pp. 149-158, 11th Mexican Conference on Pattern Recognition, MCPR 2019, Querétaro, Mexico, 26/06/19. https://doi.org/10.1007/978-3-030-21077-9_14

Rock Detection in a Mars-Like Environment Using a CNN. / Furlán, Federico; Rubio, Elsa; Sossa, Humberto et al.
Pattern Recognition - 11th Mexican Conference, MCPR 2019, Proceedings. ed. / Jesús Ariel Carrasco-Ochoa; José Francisco Martínez-Trinidad; José Arturo Olvera-López; Joaquín Salas. Springer Verlag, 2019. p. 149-158 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11524 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Rubio, Elsa

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AU - Ponce, Víctor

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N2 - In this paper we study the problem of rock detection in a Mars-like environment. We propose a convolutional neural network (CNN) to obtain a segmented image. The CNN is a modified version of the U-net architecture with a smaller number of parameters to improve the inference time. The performance of the methodology is proved in a dataset that contains several images of a Mars-like environment, achieving an F-score of 78.5%.

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KW - Convolutional neural networks

KW - Mars exploration

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A2 - Martínez-Trinidad, José Francisco

A2 - Olvera-López, José Arturo

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Furlán F, Rubio E, Sossa H, Ponce V. Rock Detection in a Mars-Like Environment Using a CNN. In Carrasco-Ochoa JA, Martínez-Trinidad JF, Olvera-López JA, Salas J, editors, Pattern Recognition - 11th Mexican Conference, MCPR 2019, Proceedings. Springer Verlag. 2019. p. 149-158. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-21077-9_14

Rock Detection in a Mars-Like Environment Using a CNN

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