1 citations · 2 across the 4 of their papers we have counts for
4 papers
Enabling On-device Continual Learning with Binary Neural Networks
Lorenzo Vorabbi, Davide Maltoni, Guido Borghi +1
On-device learning remains a formidable challenge, especially when dealing with resource-constrained devices that have limited computational capabilities. This challenge is primari…
On-Device Learning with Binary Neural Networks
Lorenzo Vorabbi, Davide Maltoni, Stefano Santi
Existing Continual Learning (CL) solutions only partially address the constraints on power, memory and computation of the deep learning models when deployed on low-power embedded C…
Input Layer Binarization with Bit-Plane Encoding
Lorenzo Vorabbi, Davide Maltoni, Stefano Santi
Binary Neural Networks (BNNs) use 1-bit weights and activations to efficiently execute deep convolutional neural networks on edge devices. Nevertheless, the binarization of the fir…
Optimizing data-flow in Binary Neural Networks
L. Vorabbi, D. Maltoni, S. Santi
Binary Neural Networks (BNNs) can significantly accelerate the inference time of a neural network by replacing its expensive floating-point arithmetic with bitwise operations. Most…