Amélie Gruel

Orcid: 0000-0003-3916-0514

According to our database1, Amélie Gruel authored at least 11 papers between 2021 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2023
Stakes of neuromorphic foveation: a promising future for embedded event cameras.
Biol. Cybern., October, 2023

Spiking neural networks for embedded event-based vision. (Réseaux de neurones impulsionnels pour la vision embarquée basée sur les événements).
PhD thesis, 2023

Performance comparison of DVS data spatial downscaling methods using Spiking Neural Networks.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Object Detection for Embedded Systems Using Tiny Spiking Neural Networks: Filtering Noise Through Visual Attention.
Proceedings of the 18th International Conference on Machine Vision and Applications, 2023

Simultaneous neuromorphic selection of multiple salient objects for event vision.
Proceedings of the International Joint Conference on Neural Networks, 2023

Frugal event data: how small is too small? A human performance assessment with shrinking data.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

End-to-end Neuromorphic Lip Reading.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Embedded neuromorphic attention model leveraging a novel low-power heterogeneous platform.
Proceedings of the 5th IEEE International Conference on Artificial Intelligence Circuits and Systems, 2023

2022
Event Data Downscaling for Embedded Computer Vision.
Proceedings of the 17th International Joint Conference on Computer Vision, 2022

Neuromorphic Event-Based Spatio-temporal Attention using Adaptive Mechanisms.
Proceedings of the 4th IEEE International Conference on Artificial Intelligence Circuits and Systems, 2022

2021
Bio-inspired visual attention for silicon retinas based on spiking neural networks applied to pattern classification.
Proceedings of the 18th International Conference on Content-Based Multimedia Indexing, 2021


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