| Designing resource-constrained neural networks using neural architecture search targeting embedded devices A Cassimon, S Vanneste, S Bosmans, S Mercelis, P Hellinckx Internet of Things 12, 100234, 2020 | 22 | 2020 |
| Introduction of deep neural network in hybrid wcet analysis T Huybrechts, A Cassimon, S Mercelis, P Hellinckx Advances on P2P, Parallel, Grid, Cloud and Internet Computing: Proceedings …, 2019 | 9 | 2019 |
| Using neural architecture search to optimize neural networks for embedded devices A Cassimon, S Vanneste, S Bosmans, S Mercelis, P Hellinckx Advances on P2P, Parallel, Grid, Cloud and Internet Computing: Proceedings …, 2020 | 6 | 2020 |
| A survey on discrete multi-objective reinforcement learning benchmarks A Cassimon, R Eyckerman, S Mercelis, S Latré, P Hellinckx Proceedings of the Adaptive and Learning Agents Workshop (ALA 2022) 2, 2022 | 4 | 2022 |
| Scalable reinforcement learning-based neural architecture search A Cassimon, S Mercelis, K Mets Neural Computing and Applications, 1-31, 2024 | 1 | 2024 |
| A Review of the Deep Sea Treasure problem as a Multi-Objective Reinforcement Learning Benchmark A Cassimon, R Eyckerman, S Mercelis, S Latré, P Hellinckx arXiv preprint arXiv:2110.06742, 2021 | 1 | 2021 |
| Designing a Classifier for Active Fire Detection from Multispectral Satellite Imagery Using Neural Architecture Search A Cassimon, P Reiter, S Mercelis, K Mets arXiv preprint arXiv:2410.05425, 2024 | | 2024 |
| Predicting Image Classifier Performance Using the Synthetic Petri Dish Method A Cassimon, L Hertoghs, S Vanneste, P Reiter, K Mets, T De Schepper, ... BNAIC/BeNeLearn 2022, 2022 | | 2022 |
Siegfried MercelisUniversity of Antwerp - imec IDLab在 uantwerpen.be 的电子邮件经过验证
