| High-accuracy wire electrical discharge machining using artificial neural networks and optimization techniques A Conde, A Arriandiaga, JA Sanchez, E Portillo, S Plaza, I Cabanes Robotics and computer-integrated manufacturing 49, 24-38, 2018 | 79 | 2018 |
| Unexpected event prediction in wire electrical discharge machining using deep learning techniques JA Sanchez, A Conde, A Arriandiaga, J Wang, S Plaza Materials 11 (7), 1100, 2018 | 31 | 2018 |
| Virtual sensors for on-line wheel wear and part roughness measurement in the grinding process A Arriandiaga, E Portillo, JA Sánchez, I Cabanes, I Pombo Sensors 14 (5), 8756-8778, 2014 | 30 | 2014 |
| Estimation of lactate threshold with machine learning techniques in recreational runners U Etxegarai, E Portillo, J Irazusta, A Arriandiaga, I Cabanes Applied Soft Computing 63, 181-196, 2018 | 23 | 2018 |
| A new approach for dynamic modelling of energy consumption in the grinding process using recurrent neural networks A Arriandiaga, E Portillo, JA Sánchez, I Cabanes, I Pombo Neural computing and applications 27, 1577-1592, 2016 | 22 | 2016 |
| Audio-visual target speaker enhancement on multi-talker environment using event-driven cameras A Arriandiaga, G Morrone, L Pasa, L Badino, C Bartolozzi 2021 IEEE International Symposium on Circuits and Systems (ISCAS), 1-5, 2021 | 15 | 2021 |
| Exploiting event cameras for spatio-temporal prediction of fast-changing trajectories M Monforte, A Arriandiaga, A Glover, C Bartolozzi 2020 2nd IEEE International Conference on Artificial Intelligence Circuits …, 2020 | 15 | 2020 |
| Pulsewidth modulation-based algorithm for spike phase encoding and decoding of time-dependent analog data A Arriandiaga, E Portillo, JI Espinosa-Ramos, NK Kasabov IEEE Transactions on Neural Networks and Learning Systems 31 (10), 3920-3931, 2019 | 15 | 2019 |
| Downsizing training data with weighted FCM for predicting the evolution of specific grinding energy with RNNs A Arriandiaga, E Portillo, JA Sánchez, I Cabanes, A Zubizarreta Applied Soft Computing 61, 211-221, 2017 | 9 | 2017 |
| Where and when: event-based spatiotemporal trajectory prediction from the iCub’s point-of-view M Monforte, A Arriandiaga, A Glover, C Bartolozzi 2020 IEEE International Conference on Robotics and Automation (ICRA), 9521-9527, 2020 | 7 | 2020 |
| Recurrent ANN-based modelling of the dynamic evolution of the surface roughness in grinding A Arriandiaga, E Portillo, JA Sánchez, I Cabanes, A Zubizarreta Neural Computing and Applications 28, 1293-1307, 2017 | 7 | 2017 |
| Optimizing Road Traffic Surveillance: A Robust Hyper-Heuristic Approach for Vehicle Segmentation E RodríGuez-Esparza, O Ramos-Soto, AD Masegosa, E Onieva, D Oliva, ... IEEE Access 12, 29503-29524, 2024 | 2 | 2024 |
| A Taxonomy of Signal Vehicle Coupled Control from a Mathematical Programming Perspective A Ghosh, JS Angarita-Zapata, AD Masegosa, AA Laresgoiti 2023 IEEE 26th International Conference on Intelligent Transportation …, 2023 | 1 | 2023 |
| Compresión de datos de tipo real basada en un novedoso algoritmo de codificación para redes neuronales de impulsos S Lucas, A Arriandiaga, E Portillo, A Zubizarreta, I Cabanes XLII Jornadas de Automática, 175-182, 2021 | 1 | 2021 |
| Modelado de la energía específica de corte en el rectificado mediante redes neuronales recurrentes A Arriandiaga, E Portillo, JA Sánchez, I Cabanes, A Zubizarreta XXXVI Jornadas de Automática: Libro de Actas, 2-4 de Septiembre de 2015 …, 2015 | | 2015 |
| On-line Surface Roughness Prediction in Grinding Using Recurrent Neural Networks A Arriandiaga, E Portillo, JA Sánchez, I Cabanes Engineering Applications of Neural Networks: 16th International Conference …, 2015 | | 2015 |
