Manuele Rusci
Manuele Rusci
MSCA Post Doc @ KU Leuven
Verified email at - Homepage
Cited by
Cited by
PULP-NN: accelerating quantized neural networks on parallel ultra-low-power RISC-V processors
A Garofalo, M Rusci, F Conti, D Rossi, L Benini
Philosophical Transactions of the Royal Society A 378 (2164), 20190155, 2020
CMix-NN: Mixed low-precision CNN library for memory-constrained edge devices
A Capotondi, M Rusci, M Fariselli, L Benini
IEEE Transactions on Circuits and Systems II: Express Briefs 67 (5), 871-875, 2020
Memory-driven mixed low precision quantization for enabling deep network inference on microcontrollers
M Rusci, A Capotondi, L Benini
Proceedings of Machine Learning and Systems 2, 326-335, 2020
A tinyml platform for on-device continual learning with quantized latent replays
L Ravaglia, M Rusci, D Nadalini, A Capotondi, F Conti, L Benini
IEEE Journal on Emerging and Selected Topics in Circuits and Systems 11 (4 …, 2021
An event-driven ultra-low-power smart visual sensor
M Rusci, D Rossi, M Lecca, M Gottardi, E Farella, L Benini
IEEE Sensors Journal 16 (13), 5344-5353, 2016
Robustifying the deployment of tinyml models for autonomous mini-vehicles
M de Prado, M Rusci, A Capotondi, R Donze, L Benini, N Pazos
Sensors 21 (4), 1339, 2021
Pulp-nn: A computing library for quantized neural network inference at the edge on risc-v based parallel ultra low power clusters
A Garofalo, M Rusci, F Conti, D Rossi, L Benini
2019 26th IEEE International Conference on Electronics, Circuits and Systems …, 2019
Work-in-progress: Quantized nns as the definitive solution for inference on low-power arm mcus?
M Rusci, A Capotondi, F Conti, L Benini
2018 International Conference on Hardware/Software Codesign and System …, 2018
A sub-mW IoT-endnode for always-on visual monitoring and smart triggering
M Rusci, D Rossi, E Farella, L Benini
IEEE Internet of Things Journal 4 (5), 1284-1295, 2017
Design automation for binarized neural networks: A quantum leap opportunity?
M Rusci, L Cavigelli, L Benini
2018 IEEE International Symposium on Circuits and Systems (ISCAS), 1-5, 2018
Leveraging automated mixed-low-precision quantization for tiny edge microcontrollers
M Rusci, M Fariselli, A Capotondi, L Benini
IoT Streams for Data-Driven Predictive Maintenance and IoT, Edge, and Mobile …, 2020
Pulp-trainlib: Enabling on-device training for risc-v multi-core mcus through performance-driven autotuning
D Nadalini, M Rusci, G Tagliavini, L Ravaglia, L Benini, F Conti
International Conference on Embedded Computer Systems, 200-216, 2022
Memory-latency-accuracy trade-offs for continual learning on a RISC-V extreme-edge node
L Ravaglia, M Rusci, A Capotondi, F Conti, L Pellegrini, V Lomonaco, ...
2020 IEEE Workshop on Signal Processing Systems (SiPS), 1-6, 2020
Low-power license plate detection and recognition on a risc-v multi-core mcu-based vision system
L Lamberti, M Rusci, M Fariselli, F Paci, L Benini
2021 IEEE International Symposium on Circuits and Systems (ISCAS), 1-5, 2021
Always-ON visual node with a hardware-software event-based binarized neural network inference engine
M Rusci, D Rossi, E Flamand, M Gottardi, E Farella, L Benini
Proceedings of the 15th ACM International Conference on Computing Frontiers …, 2018
Robust navigation with tinyML for autonomous mini-vehicles
M de Prado, R Donze, A Capotondi, M Rusci, S Monnerat, L Benini, ...
arXiv preprint arXiv:2007.00302, 2020
Towards on-device domain adaptation for noise-robust keyword spotting
C Cioflan, L Cavigelli, M Rusci, M De Prado, L Benini
2022 IEEE 4th International Conference on Artificial Intelligence Circuits …, 2022
Integer-only approximated MFCC for ultra-low power audio NN processing on multi-core MCUs
M Fariselli, M Rusci, J Cambonie, E Flamand
2021 IEEE 3rd International Conference on Artificial Intelligence Circuits …, 2021
BrightNet: A deep CNN for OLED-based point of care immunofluorescent diagnostic systems
A Samore, M Rusci, D Lazzaro, P Melpignano, L Benini, S Morigi
IEEE Transactions on Instrumentation and Measurement 69 (9), 6766-6775, 2020
The memory challenge in ultra-low power deep learning
F Conti, M Rusci, L Benini
NANO-CHIPS 2030: On-Chip AI for an Efficient Data-Driven World, 323-349, 2020
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