190 citations · 315 across the 7 of their papers we have counts for
7 papers
Bio-inspired Learning and Decision-Making with Probabilistic In-Memory Computing Hardware: Part 2
Thomas Dalgaty, Eiji Kawasaki, Miguel de Prado +3
This report extends our previous work (Part 1), which introduced an energy-based model for learning and decision-making under uncertainty. The model leverages stochastic Langevin d…
Self-Learning for Personalized Keyword Spotting on Ultra-Low-Power Audio Sensors
Manuele Rusci, Francesco Paci, Marco Fariselli +2
This paper proposes a self-learning method to incrementally train (fine-tune) a personalized Keyword Spotting (KWS) model after the deployment on ultra-low power smart audio sensor…
Scalable Hierarchical Instruction Cache for Ultra-Low-Power Processors Clusters
Jie Chen, Igor Loi, Eric Flamand +3
High Performance and Energy Efficiency are critical requirements for Internet of Things (IoT) end-nodes. Exploiting tightly-coupled clusters of programmable processors (CMPs) has r…
Accelerating RNN-based Speech Enhancement on a Multi-Core MCU with Mixed FP16-INT8 Post-Training Quantization
Manuele Rusci, Marco Fariselli, Martin Croome +2
This paper presents an optimized methodology to design and deploy Speech Enhancement (SE) algorithms based on Recurrent Neural Networks (RNNs) on a state-of-the-art MicroController…
Vega: A 10-Core SoC for IoT End-Nodes with DNN Acceleration and Cognitive Wake-Up From MRAM-Based State-Retentive Sleep Mode
Davide Rossi, Francesco Conti, Manuel Eggimann +9
The Internet-of-Things requires end-nodes with ultra-low-power always-on capability for a long battery lifetime, as well as high performance, energy efficiency, and extreme flexibi…
A 64mW DNN-based Visual Navigation Engine for Autonomous Nano-Drones
Daniele Palossi, Antonio Loquercio, Francesco Conti +3
Fully-autonomous miniaturized robots (e.g., drones), with artificial intelligence (AI) based visual navigation capabilities are extremely challenging drivers of Internet-of-Things…
A near-threshold RISC-V core with DSP extensions for scalable IoT Endpoint Devices
Michael Gautschi, Pasquale Davide Schiavone, Andreas Traber +6
Endpoint devices for Internet-of-Things not only need to work under extremely tight power envelope of a few milliwatts, but also need to be flexible in their computing capabilities…