| A survey of artificial neural network training tools D Baptista, F Morgado-Dias Neural Computing and Applications 23, 609-615, 2013 | 47 | 2013 |
| Performance comparison of ANN training algorithms for classification FD Baptista, S Rodrigues, F Morgado-Dias 2013 IEEE 8th International Symposium on Intelligent Signal Processing, 115-120, 2013 | 46 | 2013 |
| Implementation strategy of convolution neural networks on field programmable gate arrays for appliance classification using the voltage and current (VI) trajectory D Baptista, SS Mostafa, L Pereira, L Sousa, F Morgado-Dias Energies 11 (9), 2460, 2018 | 42 | 2018 |
| Hardware implementation of an artificial neural network model to predict the energy production of a photovoltaic system D Baptista, S Abreu, C Travieso-Gonzalez, F Morgado-Dias Microprocessors and Microsystems 49, 77-86, 2017 | 29 | 2017 |
| Low-resource hardware implementation of the hyperbolic tangent for artificial neural networks D Baptista, F Morgado-Dias Neural Computing and Applications 23, 601-607, 2013 | 26 | 2013 |
| Automatic general-purpose neural hardware generator FD Baptista, F Morgado-Dias Neural Computing and Applications 28, 25-36, 2017 | 25 | 2017 |
| A survey of software and hardware use in artificial neural networks D Baptista, S Abreu, F Freitas, R Vasconcelos, F Morgado-Dias Neural Computing and Applications 23, 591-599, 2013 | 24 | 2013 |
| Greedy based convolutional neural network optimization for detecting apnea SS Mostafa, D Baptista, AG Ravelo-García, G Juliá-Serdá, ... Computer Methods and Programs in Biomedicine 197, 105640, 2020 | 21 | 2020 |
| Comparing different solutions for forecasting the energy production of a wind farm D Baptista, JP Carvalho, F Morgado-Dias Neural Computing and Applications, 1-9, 2018 | 15 | 2018 |
| A software tool for automatic generation of neural hardware L Reis, L Aguiar, D Baptista, F Morgado-Dias Neuron 1 (1), 229-235, 2014 | 12 | 2014 |
| Comparing different implementations for the Levenberg-Marquardt algorithm D Baptista, M Dias CONTROLO’2012, 2012 | 9 | 2012 |
| A Platform based on HLS to Implement a Generic CNN on an FPGA D Baptista, F Morgado-Dias, L Sousa 2019 International Conference in Engineering Applications (ICEA), 1-7, 2019 | 7 | 2019 |
| Configurable N-fold hardware architecture for convolutional neural networks D Baptista, F Morgado-Dias, L Sousa 2018 International Conference on Biomedical Engineering and Applications …, 2018 | 7 | 2018 |
| Simulação do comportamento espectral de redes de período longo em fibra óptica FDV Baptista PQDT-Global, 2009 | 7 | 2009 |
| Raising the abstraction level of a deep learning design on FPGAs D Baptista, L Sousa, F Morgado-Dias IEEE Access 8, 205148-205161, 2020 | 6 | 2020 |
| ANGE–Automatic Neural Generator L Reis, L Aguiar, D Baptista, F Morgado Dias Artificial Neural Networks and Machine Learning–ICANN 2011: 21st …, 2011 | 6 | 2011 |
| On the implementation of different hyperbolic tangent solutions in FPGA D Baptista, M Dias CONTROLO’2012, 2012 | 4 | 2012 |
| ARTIFICIAL NEURAL NETWORKS â A SURVEY ABOUT HARDWARE AND SOFTWARE USE D Baptista, F Freitas, M Dias, R Vasconcelos CONTROLO’2012, 2012 | 3 | 2012 |
| Energy production forecasting for a wind farm composed of turbines with different features D Baptista, F Morgado-Dias 2017 International Conference in Energy and Sustainability in Small …, 2017 | 2 | 2017 |
| Automatic Control of Madeira Wine Aging Process CM Faria, D Baptista, JC Marques, F Morgado-Dias CONTROLO 2016: Proceedings of the 12th Portuguese Conference on Automatic …, 2017 | 2 | 2017 |
Morgado-DiasAssociate Professor at the University of Madeira, Interactive Technologies Institute (ITI/LARSyS)Verified email at uma.pt
