Matteo Grimaldi

According to our database, Matteo Grimaldi authored at least 11 papers between 2018 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2026

Symmetry-Aware Fusion of Vision and Tactile Sensing via Bilateral Force Priors for Robotic Manipulation.

Wonju Lee, Matteo Grimaldi, Tao Yu

CoRR, February, 2026

2024

MCUBench: A Benchmark of Tiny Object Detectors on MCUs.

Sudhakar Sah, Darshan C. Ganji, Matteo Grimaldi, Ravish Kumar, Alexander Hoffman, Honnesh Rohmetra, Ehsan Saboori

Proceedings of the Computer Vision - ECCV 2024 Workshops, 2024

2023

Dynamic ConvNets on Tiny Devices via Nested Sparsity.

Matteo Grimaldi, Luca Mocerino, Antonio Cipolletta, Andrea Calimera

IEEE Internet Things J., 2023

YOLOBench: Benchmarking Efficient Object Detectors on Embedded Systems.

Ivan Lazarevich, Matteo Grimaldi, Ravish Kumar, Saptarshi Mitra, Shahrukh Khan, Sudhakar Sah

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Accelerating Deep Neural Networks via Semi-Structured Activation Sparsity.

Matteo Grimaldi, Darshan C. Ganji, Ivan Lazarevich, Sudhakar Sah Deeplite

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2021

Hardware-Aware Compression Techniques for Embedded Deep Neural Networks.

Matteo Grimaldi

PhD thesis, 2021

2020

EAST: Encoding-Aware Sparse Training for Deep Memory Compression of ConvNets.

Matteo Grimaldi, Valentino Peluso, Andrea Calimera

Proceedings of the 2nd IEEE International Conference on Artificial Intelligence Circuits and Systems, 2020

2019

Layer-Wise Compressive Training for Convolutional Neural Networks.

Matteo Grimaldi, Valerio Tenace, Andrea Calimera

Future Internet, 2019

Optimality Assessment of Memory-Bounded ConvNets Deployed on Resource-Constrained RISC Cores.

Matteo Grimaldi, Valentino Peluso, Andrea Calimera

IEEE Access, 2019

Arbitrary-Precision Convolutional Neural Networks on Low-Power IoT Processors.

Valentino Peluso, Matteo Grimaldi, Andrea Calimera

Proceedings of the 27th IFIP/IEEE International Conference on Very Large Scale Integration, 2019

2018

A compression-driven training framework for embedded deep neural networks.

Matteo Grimaldi, Federico Pugliese, Valerio Tenace, Andrea Calimera

Proceedings of the Workshop on INTelligent Embedded Systems Architectures and Applications, 2018