2 citations · 2 across the 2 of their papers we have counts for
4 papers
Always-On 674uW @ 4GOP/s Error Resilient Binary Neural Networks with Aggressive SRAM Voltage Scaling on a 22nm IoT End-Node
Alfio Di Mauro, Francesco Conti, Pasquale Davide Schiavone +2
Binary Neural Networks (BNNs) have been shown to be robust to random bit-level noise, making aggressive voltage scaling attractive as a power-saving technique for both logic and SR…
Arnold: an eFPGA-Augmented RISC-V SoC for Flexible and Low-Power IoT End-Nodes
Pasquale Davide Schiavone, Davide Rossi, Alfio Di Mauro +5
A wide range of Internet of Things (IoT) applications require powerful, energy-efficient and flexible end-nodes to acquire data from multiple sources, process and distill the sense…
XNOR Neural Engine: a Hardware Accelerator IP for 21.6 fJ/op Binary Neural Network Inference
Francesco Conti, Pasquale Davide Schiavone, Luca Benini
Binary Neural Networks (BNNs) are promising to deliver accuracy comparable to conventional deep neural networks at a fraction of the cost in terms of memory and energy. In this pap…
Fast and Accurate Multiclass Inference for MI-BCIs Using Large Multiscale Temporal and Spectral Features
Michael Hersche, Tino Rellstab, Pasquale Davide Schiavone +3
Accurate, fast, and reliable multiclass classification of electroencephalography (EEG) signals is a challenging task towards the development of motor imagery brain-computer interfa…