Ferran Parés

According to our database, Ferran Parés authored at least 16 papers between 2017 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2022

The MAMe dataset: on the relevance of high resolution and variable shape image properties.

Ferran Parés, Anna Arias-Duart, Dario Garcia-Gasulla, Gema Campo-Francés, Nina Viladrich, Eduard Ayguadé, Jesús Labarta

Appl. Intell., 2022

Focus! Rating XAI Methods and Finding Biases.

Anna Arias-Duart, Ferran Parés, Dario Garcia-Gasulla, Victor Gimenez-Abalos

Proceedings of the IEEE International Conference on Fuzzy Systems, 2022

Focus and Bias: Will It Blend?

Anna Arias-Duart, Ferran Parés, Víctor Giménez-Ábalos, Dario Garcia-Gasulla

Proceedings of the Artificial Intelligence Research and Development, 2022

2021

Size & Shape Matters: The Need of HPC Benchmarks of High Resolution Image Training for Deep Learning.

Ferran Parés Pont, Pedro Megias, Dario Garcia-Gasulla, Marta Garcia-Gasulla, Eduard Ayguadé, Jesús Labarta

Supercomput. Front. Innov., 2021

Who Explains the Explanation? Quantitatively Assessing Feature Attribution Methods.

Anna Arias-Duart, Ferran Parés, Dario Garcia-Gasulla

CoRR, 2021

2020

A Closer Look at Art Mediums: The MAMe Image Classification Dataset.

Ferran Parés, Anna Arias-Duart, Dario Garcia-Gasulla, Gema Campo-Francés, Nina Viladrich, Eduard Ayguadé, Jesús Labarta

CoRR, 2020

2019

Studying the impact of the Full-Network embedding on multimodal pipelines.

Armand Vilalta, Dario Garcia-Gasulla, Ferran Parés, Eduard Ayguadé, Jesús Labarta, Eduardo Ulises Moya-Sánchez, Ulises Cortés

Semantic Web, 2019

Random Forest as a Tumour Genetic Marker Extractor.

Raquel Pérez-Arnal, Dario Garcia-Gasulla, David Torrents, Ferran Parés, Ulises Cortés, Jesús Labarta, Eduard Ayguadé

Proceedings of the Artificial Intelligence Research and Development, 2019

2018

On the Behavior of Convolutional Nets for Feature Extraction.

Dario Garcia-Gasulla, Ferran Parés, Armand Vilalta, Jonathan Moreno, Eduard Ayguadé, Jesús Labarta, Ulises Cortés, Toyotaro Suzumura

J. Artif. Intell. Res., 2018

An Out-of-the-box Full-Network Embedding for Convolutional Neural Networks.

Dario Garcia-Gasulla, Armand Vilalta, Ferran Parés, Eduard Ayguadé, Jesús Labarta, Ulises Cortés, Toyotaro Suzumura

Proceedings of the 2018 IEEE International Conference on Big Knowledge, 2018

2017

Full-Network Embedding in a Multimodal Embedding Pipeline.

Armand Vilalta, Dario Garcia-Gasulla, Ferran Parés, Eduard Ayguadé, Jesús Labarta, Ulises Cortés, Toyotaro Suzumura

CoRR, 2017

Fluid Communities: A Community Detection Algorithm.

Ferran Parés, Dario Garcia-Gasulla, Armand Vilalta, Jonathan Moreno, Eduard Ayguadé, Jesús Labarta, Ulises Cortés, Toyotaro Suzumura

CoRR, 2017

An Out-of-the-box Full-network Embedding for Convolutional Neural Networks.

Dario Garcia-Gasulla, Armand Vilalta, Ferran Parés, Jonathan Moreno, Eduard Ayguadé, Jesús Labarta, Ulises Cortés, Toyotaro Suzumura

CoRR, 2017

Full-Network Embedding in a Multimodal Embedding Pipeline.

Armand Vilalta, Dario Garcia-Gasulla, Ferran Parés, Jonathan Moreno, Eduard Ayguadé, Jesús Labarta, Ulises Cortés, Toyotaro Suzumura

Proceedings of the 2nd Workshop on Semantic Deep Learning, 2017

Building Graph Representations of Deep Vector Embeddings.

Dario Garcia-Gasulla, Armand Vilalta, Ferran Parés, Jonathan Moreno, Eduard Ayguadé, Jesús Labarta, Ulises Cortés, Toyotaro Suzumura

Proceedings of the 2nd Workshop on Semantic Deep Learning, 2017

Fluid Communities: A Competitive, Scalable and Diverse Community Detection Algorithm.

Ferran Parés, Dario Garcia-Gasulla, Armand Vilalta, Jonathan Moreno, Eduard Ayguadé, Jesús Labarta, Ulises Cortés, Toyotaro Suzumura

Proceedings of the Complex Networks & Their Applications VI, 2017