| Machine learning and deep learning frameworks and libraries for large-scale data mining: a survey G Nguyen, S Dlugolinsky, M Bobák, V Tran, Á López García, I Heredia, ... Artificial Intelligence Review 52, 77-124, 2019 | 834 | 2019 |
| A cloud-based framework for machine learning workloads and applications ÁL García, JM De Lucas, M Antonacci, W Zu Castell, M David, M Hardt, ... IEEE access 8, 18681-18692, 2020 | 91 | 2020 |
| Large-scale plant classification with deep neural networks I Heredia Proceedings of the computing frontiers conference, 259-262, 2017 | 33 | 2017 |
| Application of a Convolutional Neural Network for image classification for the analysis of collisions in High Energy Physics CF Madrazo, I Heredia, L Lloret, JM de Lucas EPJ Web of Conferences 214, 06017, 2019 | 27 | 2019 |
| Forecasting COVID-19 spreading through an ensemble of classical and machine learning models: Spain’s case study I Heredia Cacha, J Sáinz-Pardo Díaz, M Castrillo, Á López García Scientific Reports 13 (1), 6750, 2023 | 9 | 2023 |
| Artificial intelligence to estimate wine volume from single-view images M Cobo, I Heredia, F Aguilar, LL Iglesias, D García, B Bartolomé, ... Heliyon 8 (9), 2022 | 8 | 2022 |
| Convolutional Neural Networks for Phytoplankton identification and classification L Lloret, I Heredia, F Aguilar, E Debusschere, K Deneudt, F Hernandez Biodiversity Information Science and Standards 2, e25762, 2018 | 7 | 2018 |
| BrainGut_WineUp daily lifelike images [Dataset] B Bartolomé, M Moreno-Arribas, L Lloret Iglesias, F Aguilar, M Cobo Cano, ... DIGITAL. CSIC, 2022 | 3 | 2022 |
| BrainGut_WineUp laboratory images [Dataset] B Bartolomé, MV Moreno-Arribas, L Lloret, F Aguilar, M Cobo, D García, ... | 3* | 2021 |
| Plants classification engine I Heredia, L Lloret Iglesias | 2 | 2019 |
| Image classification engine I Heredia | 2 | 2019 |
| Deep learning for weed identification based on seed images F Pando, I Heredia, CA Pérez, MV Rodríguez, LL Iglesias, J Calvo Biodiversity Information Science and Standards 2, e25749, 2018 | 2 | 2018 |
| Novel deep learning method for coronary artery tortuosity detection through coronary angiography M Cobo, F Pérez-Rojas, C Gutiérrez-Rodríguez, I Heredia, ... Scientific reports 13 (1), 11137, 2023 | 1 | 2023 |
| Use-case of Deep Generative Models for Perfect Prognosis Climate Downscaling J González-Abad, J Baño-Medina, I Heredia CSIC-UC-Instituto de Física de Cantabria (IFCA), 2021 | 1 | 2021 |
| Seeds classification engine I Heredia, L Lloret Iglesias | 1 | 2018 |
| Novel digital-based approach for evaluating wine components´ intake: a deep learning model to determine red wine volume in a glass from single-view images M Cobo, ER de la Guía, I Heredia, F Aguilar, L Lloret-Iglesias, D García, ... Heliyon, 2024 | | 2024 |
| Personalized Federated Learning for improving radar based precipitation nowcasting on heterogeneous areas J Sáinz-Pardo Díaz, M Castrillo, J Bartok, I Heredia Cachá, I Malkin Ondík, ... arXiv e-prints, arXiv: 2408.05761, 2024 | | 2024 |
| Making Federated Learning Accessible to Scientists: The AI4EOSC Approach J Sáinz-Pardo Díaz, A Heredia Canales, I Heredia Cachá, V Tran, ... Proceedings of the 2024 ACM Workshop on Information Hiding and Multimedia …, 2024 | | 2024 |
| Novel approach based on artificial intelligence to evaluate individual wine intake M Cobo Cano, E Regaño de la Guía, I Heredia, F Aguilar, L Lloret Iglesias, ... EDP Sciences, 2023 | | 2023 |
| Novel deep learning method for coronary artery tortuosity detection through coronary angiography M Cobo Cano, F Pérez-Rojas, C Gutiérrez-Rodríguez, I Heredia, ... Springer Nature, 2023 | | 2023 |
