| Artificial neural network modelling of the antioxidant activity and phenolic compounds of bananas submitted to different drying treatments RPF Guiné, MJ Barroca, FJ Gonçalves, M Alves, S Oliveira, M Mendes Food Chemistry 168, 454-459, 2015 | 142 | 2015 |
| Augmented reality maintenance assistant using yolov5 A Malta, M Mendes, T Farinha Applied Sciences 11 (11), 4758, 2021 | 120 | 2021 |
| Comparing LSTM and GRU models to predict the condition of a pulp paper press BC Mateus, M Mendes, JT Farinha, R Assis, AM Cardoso Energies 14 (21), 6958, 2021 | 115 | 2021 |
| Predicting motor oil condition using artificial neural networks and principal component analysis J RodRigues, I Costa, JT Farinha, M Mendes, L Margalho Eksploatacja i Niezawodność 22 (3), 2020 | 45 | 2020 |
| Modelling the influence of origin, packing and storage on water activity, colour and texture of almonds, hazelnuts and walnuts using artificial neural networks RPF Guiné, CFF Almeida, PMR Correia, M Mendes Food and Bioprocess Technology 8, 1113-1125, 2015 | 42 | 2015 |
| Wind farm and resource datasets: A comprehensive survey and overview D Menezes, M Mendes, JA Almeida, T Farinha Energies 13 (18), 4702, 2020 | 39 | 2020 |
| Convective drying of apples: kinetic study, evaluation of mass transfer properties and data analysis using artificial neural networks RPF Guiné, AC Cruz, M Mendes International Journal of Food Engineering 10 (2), 281-299, 2014 | 33 | 2014 |
| Anticipating future behavior of an industrial press using LSTM networks BC Mateus, M Mendes, JT Farinha, AM Cardoso Applied Sciences 11 (13), 6101, 2021 | 32 | 2021 |
| Robot navigation using a sparse distributed memory M Mendes, M Crisóstomo, AP Coimbra 2008 IEEE International Conference on Robotics and Automation, 53-58, 2008 | 30 | 2008 |
| Experiments with assessment of creative systems: an application of Ritchie’s criteria FC Pereira, M Mendes, P Gervás, A Cardoso Proceedings of the workshop on computational creativity, 19th international …, 2005 | 26 | 2005 |
| Assessing a sparse distributed memory using different encoding methods M Mendes, MM Crisóstomo, AP Coimbra Proceedings of the world congress on engineering 1, 1-6, 2009 | 25 | 2009 |
| Short and long forecast to implement predictive maintenance in a pulp industry JA Rodrigues, JT Farinha, M Mendes, R Mateus, AM Cardoso Eksploatacja i Niezawodność 24 (1), 2022 | 24 | 2022 |
| Offline handwritten signature verification using deep neural networks JAP Lopes, B Baptista, N Lavado, M Mendes Energies 15 (20), 7611, 2022 | 21 | 2022 |
| Counting people and bicycles in real time using YOLO on Jetson Nano H Gomes, N Redinha, N Lavado, M Mendes Energies 15 (23), 8816, 2022 | 20 | 2022 |
| Evaluation of phenolic compounds and antioxidant activity of blueberries and modelization by artificial neural networks RPF Guiné, S Matos, FJ Gonçalves, D Costa, M Mendes International Journal of Fruit Science 18 (2), 199-214, 2018 | 19 | 2018 |
| Real-time quality control of heat sealed bottles using thermal images and artificial neural network S Cruz, A Paulino, J Duraes, M Mendes Journal of Imaging 7 (2), 24, 2021 | 18 | 2021 |
| Influence of sociodemographic factors on eating motivations–modelling through artificial neural networks (ANN) RPF Guiné, AC Ferrão, M Ferreira, P Correia, M Mendes, E Bartkiene, ... International journal of food sciences and nutrition 71 (5), 614-627, 2020 | 18 | 2020 |
| Projected augmented reality intelligent model of a city area with path optimization M Mendes, J Almeida, H Mohamed, R Giot Algorithms 12 (7), 140, 2019 | 18 | 2019 |
| Robot navigation and manipulation based on a predictive associative memory S Jockel, M Mendes, J Zhang, AP Coimbra, M Crisóstomo 2009 IEEE 8th International Conference on Development and Learning, 1-7, 2009 | 18 | 2009 |
| Movement detection and moving object distinction based on optical flow PAS Mendes, M Mendes, AP Coimbra, MM Crisóstomo Transactions on Engineering Technologies: World Congress on Engineering 2019 …, 2020 | 17 | 2020 |
