A First Glance into Reversing Senescence on Herbarium Sample Images Through Conditional Generative Adversarial Networks

Juan Villacis-Llobet; Marco Lucio-Troya; Marvin Calvo-Navarro; Saul Calderon-Ramirez; Erick Mata-Montero

doi:10.1007/978-3-030-41005-6_30

A First Glance into Reversing Senescence on Herbarium Sample Images Through Conditional Generative Adversarial Networks

Juan Villacis-Llobet, Marco Lucio-Troya, Marvin Calvo-Navarro, Saul Calderon-Ramirez, Erick Mata-Montero

Costa Rica Institute of Technology

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

4 Citas (Scopus)

Resumen

In this paper we describe a novel approach to perform senescense reversal on photos of leaves based on Conditional Generative Adversarial Networks, which have been used succesfully to perform similar tasks on faces of humans and other picture to picture translations. We show that their use can lead to a valid solution to this problem, as long as the task of creating a large and comprehensive dataset is surpassed. Additionally, we present a new dataset that consists of 120 paired photos of leaves manually collected for this work, in their fresh and senescenced states. We used the structure similarity index to compare the ground truth with the generated images and yielded an average of 0.9.

Idioma original	Inglés
Título de la publicación alojada	High Performance Computing - 6th Latin American Conference, CARLA 2019, Revised Selected Papers
Editores	Juan Luis Crespo-Mariño, Esteban Meneses-Rojas
Editorial	Springer
Páginas	438-447
Número de páginas	10
ISBN (versión impresa)	9783030410049
DOI	https://doi.org/10.1007/978-3-030-41005-6_30
Estado	Publicada - 2020
Evento	6th Latin American High Performance Computing Conference, CARLA 2019 - Turrialba, Costa Rica Duración: 25 sept 2019 → 27 sept 2019

Serie de la publicación

Nombre	Communications in Computer and Information Science
Volumen	1087 CCIS
ISSN (versión impresa)	1865-0929
ISSN (versión digital)	1865-0937

Conferencia

Conferencia	6th Latin American High Performance Computing Conference, CARLA 2019
País/Territorio	Costa Rica
Ciudad	Turrialba
Período	25/09/19 → 27/09/19

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10.1007/978-3-030-41005-6_30

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Villacis-Llobet, J., Lucio-Troya, M., Calvo-Navarro, M., Calderon-Ramirez, S., & Mata-Montero, E. (2020). A First Glance into Reversing Senescence on Herbarium Sample Images Through Conditional Generative Adversarial Networks. En J. L. Crespo-Mariño, & E. Meneses-Rojas (Eds.), High Performance Computing - 6th Latin American Conference, CARLA 2019, Revised Selected Papers (pp. 438-447). (Communications in Computer and Information Science; Vol. 1087 CCIS). Springer. https://doi.org/10.1007/978-3-030-41005-6_30

Villacis-Llobet, Juan ; Lucio-Troya, Marco ; Calvo-Navarro, Marvin et al. / A First Glance into Reversing Senescence on Herbarium Sample Images Through Conditional Generative Adversarial Networks. High Performance Computing - 6th Latin American Conference, CARLA 2019, Revised Selected Papers. editor / Juan Luis Crespo-Mariño ; Esteban Meneses-Rojas. Springer, 2020. pp. 438-447 (Communications in Computer and Information Science).

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title = "A First Glance into Reversing Senescence on Herbarium Sample Images Through Conditional Generative Adversarial Networks",

abstract = "In this paper we describe a novel approach to perform senescense reversal on photos of leaves based on Conditional Generative Adversarial Networks, which have been used succesfully to perform similar tasks on faces of humans and other picture to picture translations. We show that their use can lead to a valid solution to this problem, as long as the task of creating a large and comprehensive dataset is surpassed. Additionally, we present a new dataset that consists of 120 paired photos of leaves manually collected for this work, in their fresh and senescenced states. We used the structure similarity index to compare the ground truth with the generated images and yielded an average of 0.9.",

keywords = "Bioinformatics, Conditional-GANs, Herbaria, Senescence",

author = "Juan Villacis-Llobet and Marco Lucio-Troya and Marvin Calvo-Navarro and Saul Calderon-Ramirez and Erick Mata-Montero",

note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG.; 6th Latin American High Performance Computing Conference, CARLA 2019 ; Conference date: 25-09-2019 Through 27-09-2019",

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doi = "10.1007/978-3-030-41005-6_30",

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Villacis-Llobet, J, Lucio-Troya, M, Calvo-Navarro, M, Calderon-Ramirez, S & Mata-Montero, E 2020, A First Glance into Reversing Senescence on Herbarium Sample Images Through Conditional Generative Adversarial Networks. En JL Crespo-Mariño & E Meneses-Rojas (eds.), High Performance Computing - 6th Latin American Conference, CARLA 2019, Revised Selected Papers. Communications in Computer and Information Science, vol. 1087 CCIS, Springer, pp. 438-447, 6th Latin American High Performance Computing Conference, CARLA 2019, Turrialba, Costa Rica, 25/09/19. https://doi.org/10.1007/978-3-030-41005-6_30

A First Glance into Reversing Senescence on Herbarium Sample Images Through Conditional Generative Adversarial Networks. / Villacis-Llobet, Juan; Lucio-Troya, Marco; Calvo-Navarro, Marvin et al.
High Performance Computing - 6th Latin American Conference, CARLA 2019, Revised Selected Papers. ed. / Juan Luis Crespo-Mariño; Esteban Meneses-Rojas. Springer, 2020. p. 438-447 (Communications in Computer and Information Science; Vol. 1087 CCIS).

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

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T1 - A First Glance into Reversing Senescence on Herbarium Sample Images Through Conditional Generative Adversarial Networks

AU - Villacis-Llobet, Juan

AU - Lucio-Troya, Marco

AU - Calvo-Navarro, Marvin

AU - Calderon-Ramirez, Saul

AU - Mata-Montero, Erick

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N2 - In this paper we describe a novel approach to perform senescense reversal on photos of leaves based on Conditional Generative Adversarial Networks, which have been used succesfully to perform similar tasks on faces of humans and other picture to picture translations. We show that their use can lead to a valid solution to this problem, as long as the task of creating a large and comprehensive dataset is surpassed. Additionally, we present a new dataset that consists of 120 paired photos of leaves manually collected for this work, in their fresh and senescenced states. We used the structure similarity index to compare the ground truth with the generated images and yielded an average of 0.9.

AB - In this paper we describe a novel approach to perform senescense reversal on photos of leaves based on Conditional Generative Adversarial Networks, which have been used succesfully to perform similar tasks on faces of humans and other picture to picture translations. We show that their use can lead to a valid solution to this problem, as long as the task of creating a large and comprehensive dataset is surpassed. Additionally, we present a new dataset that consists of 120 paired photos of leaves manually collected for this work, in their fresh and senescenced states. We used the structure similarity index to compare the ground truth with the generated images and yielded an average of 0.9.

KW - Bioinformatics

KW - Conditional-GANs

KW - Herbaria

KW - Senescence

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Villacis-Llobet J, Lucio-Troya M, Calvo-Navarro M, Calderon-Ramirez S, Mata-Montero E. A First Glance into Reversing Senescence on Herbarium Sample Images Through Conditional Generative Adversarial Networks. En Crespo-Mariño JL, Meneses-Rojas E, editores, High Performance Computing - 6th Latin American Conference, CARLA 2019, Revised Selected Papers. Springer. 2020. p. 438-447. (Communications in Computer and Information Science). doi: 10.1007/978-3-030-41005-6_30

A First Glance into Reversing Senescence on Herbarium Sample Images Through Conditional Generative Adversarial Networks

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