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iMagine Publications

This page collects the publications acknowledging iMagine that were published throughout the project.
Image

NB: the links are to journals when an Open Access version exists, or to the repository where the full texts are available.

2024
2023
2022

2024

Aishwarya Venkataramanan, Michael Kloster, Andrea Burfeid-Castellanos, Mimoza Dani, Ntambwe A S Mayombo, Danijela Vidakovic, Daniel Langenkämper, Mingkun Tan, Cedric Pradalier, Tim Nattkemper, Martin Laviale, Bánk Beszteri, “UDE DIATOMS in the Wild 2024”: a new image dataset of freshwater diatoms for training deep learning models, GigaScience, Volume 13, 2024, giae087

Gayá-Vilar, Alberto, Alberto Abad-Uribarren, Augusto Rodríguez-Basalo, Pilar Ríos, Javier Cristobo, and Elena Prado. 2024. “Deep Learning Based Characterization of Cold-Water Coral Habitat at Central Cantabrian Natura 2000 Sites Using YOLOv8” Journal of Marine Science and Engineering 12, no. 9: 1617.

Prat, O. [et al.]. AI-based fish detection and classification at OBSEA underwater observatory. “International Conference on Marine Data and Information Systems: proceedings, volume Miscellanea INGV, 80”. Roma: Istituto Nazionale di Geofisica e Vulcanologia (INGV), 2024, p. 50-52. ISBN 2039-6651.

Publisher version.
Falahzadehabarghouee, A. [et al.]. Detect and follow a custom object, using OBSEA underwater crawler. 11th International Workshop on Marine Technology (MARTECH 2024). “Instrumentation viewpoint”, 2024, núm. 23, p. 86-87.
Baños Castelló, P. [et al.]. Evaluating the biological impact of an artificial reef using deep learning techniques. 11th International Workshop on Marine Technology (MARTECH 2024). “Instrumentation viewpoint”, 2024, núm. 23, p. 59-60.
Prat Bayarri, O. [et al.]. Tools for ecosystem monitoring based on fish detection and classification using deep neural networks. 11th International Workshop on Marine Technology (MARTECH 2024). “Instrumentation viewpoint”, 2024, núm. 23, p. 74-75.

2023

Aishwarya Venkataramanan, Assia Benbihi, Martin Laviale, Cédric Pradalier. Gaussian Latent Representations for Uncertainty Estimation using Mahalanobis Distance in Deep Classifiers. 2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW), Oct 2023, Paris, France. pp.4490-4499, doi: 10.1109/ICCVW60793.2023.00483.

Aishwarya Venkataramanan, Martin Laviale, Cédric Pradalier. Integrating Visual and Semantic Similarity Using Hierarchies for Image Retrieval. Computer Vision Systems. ICVS 2023, Sep 2023, Vienne (AUT), Austria. pp.422-431, doi: 10.1007/978-3-031-44137-0_35

2022

Aishwarya Venkataramanan, Pierre Faure-Giovagnoli, Cyril Regan, David Heudre, Cécile Figus, et al.. Usefulness of synthetic datasets for diatom automatic detection using a deep-learning approach. Engineering Applications of Artificial Intelligence, 2023, 117, pp.105594. 10.1016/j.engappai.2022.105594