@inproceedings{c06a55681fdf4c11957110a7f48461c2,
title = "Rock Detection in a Mars-Like Environment Using a CNN",
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",
note = "Publisher Copyright: {\textcopyright} 2019, Springer Nature Switzerland AG.; 11th Mexican Conference on Pattern Recognition, MCPR 2019 ; Conference date: 26-06-2019 Through 29-06-2019",
year = "2019",
month = jan,
day = "1",
doi = "10.1007/978-3-030-21077-9_14",
language = "Ingl{\'e}s",
isbn = "9783030210762",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "149--158",
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",
booktitle = "Pattern Recognition - 11th Mexican Conference, MCPR 2019, Proceedings",
address = "Alemania",
}