| Constrained evolutionary piecemeal training to design convolutional neural networks D Sapra, AD Pimentel Trends in Artificial Intelligence Theory and Applications. Artificial …, 2020 | 30 | 2020 |
| Optimization and deployment of CNNs at the edge: the ALOHA experience P Meloni, D Loi, P Busia, G Deriu, AD Pimentel, D Sapra, T Stefanov, ... Proceedings of the 16th ACM international conference on computing frontiers …, 2019 | 17 | 2019 |
| ALOHA: an architectural-aware framework for deep learning at the edge P Meloni, D Loi, G Deriu, AD Pimentel, D Sapra, B Moser, N Shepeleva, ... Proceedings of the workshop on INTelligent embedded systems architectures …, 2018 | 17 | 2018 |
| CPU-GPU layer-switched low latency CNN inference E Aghapour, D Sapra, A Pimentel, A Pathania 2022 25th Euromicro Conference on Digital System Design (DSD), 324-331, 2022 | 15 | 2022 |
| An evolutionary optimization algorithm for gradually saturating objective functions D Sapra, AD Pimentel Proceedings of the 2020 Genetic and Evolutionary Computation Conference, 886-893, 2020 | 13 | 2020 |
| Deep learning model reuse and composition in knowledge centric networking D Sapra, AD Pimentel 2020 29th International Conference on Computer Communications and Networks …, 2020 | 12 | 2020 |
| Scenario based run-time switching for adaptive CNN-based applications at the edge S Minakova, D Sapra, T Stefanov, AD Pimentel ACM Transactions on Embedded Computing Systems (TECS) 21 (2), 1-33, 2022 | 11 | 2022 |
| Designing convolutional neural networks with constrained evolutionary piecemeal training D Sapra, AD Pimentel Applied Intelligence 52 (15), 17103-17117, 2022 | 9 | 2022 |
| On Achieving Privacy-Preserving State-of-the-Art Edge Intelligence C Daphnee, S Dolly, Z Ádám Mann arXiv e-prints, arXiv: 2302.05323, 2023 | 5* | 2023 |
| ARM-CO-UP: ARM COoperative Utilization of Processors E Aghapour, D Sapra, A Pimentel, A Pathania ACM Transactions on Design Automation of Electronic Systems, 2024 | 3 | 2024 |
| Exploring Multi-core Systems with Lifetime Reliability and Power Consumption Trade-offs D Sapra, AD Pimentel Embedded Computer Systems: Architectures, Modeling, and Simulation: 23rd …, 2023 | 3 | 2023 |
| Architecture-aware design and implementation of CNN algorithms for embedded inference: the ALOHA project P Meloni, D Loi, G Deriu, AD Pimentel, D Saprat, M Pintort, B Biggio, ... 2018 30th International Conference on Microelectronics (ICM), 52-55, 2018 | 3 | 2018 |
| PELSI: Power-Efficient Layer-Switched Inference E Aghapour, D Sapra, AD Pimentel, A Pathania 2023 IEEE 29th International Conference on Embedded and Real-Time Computing …, 2023 | 2 | 2023 |
| Exploring cell-based neural architectures for embedded systems I van Ipenburg, D Sapra, AD Pimentel Joint European Conference on Machine Learning and Knowledge Discovery in …, 2021 | 2 | 2021 |
| Work-in-progress: Design-space exploration of multi-core processors for safety-critical real-time systems D Sapra, S Altmeyer 2017 IEEE Real-Time Systems Symposium (RTSS), 360-362, 2017 | 2 | 2017 |
| PiQi: Partially Quantized DNN Inference on HMPSoCs E Aghapour, Y Shen, D Sapra, A Pimentel, A Pathania Proceedings of the 29th ACM/IEEE International Symposium on Low Power …, 2024 | 1 | 2024 |
| The admorph approach for adaptively morphing embedded systems A Pimentel, C Grelck, L Miedema, D Sapra, M Völp, F Lucchetti, A Matovic, ... ACM SIGAda Ada Letters 43 (2), 78-83, 2024 | 1 | 2024 |
| The Choice of AI Matters: Alternative Machine Learning Approaches for CPS Anomalies U Odyurt, D Sapra, AD Pimentel Advances and Trends in Artificial Intelligence. From Theory to Practice …, 2021 | 1 | 2021 |
| Efficient neural architectures for edge devices D Sapra University of Amsterdam, 2022 | | 2022 |
| ALOHA P MELONI, O Ripolles, D Solans, M Pintor, B Biggio, T Stefanov, ... Proceedings of the Workshop on INTelligent Embedded Systems Architectures …, 0 | | |
Andy D. PimentelProfessor of Computer Science, University of AmsterdamEmail verificata su uva.nl