7 citations · 7 across the 5 of their papers we have counts for
5 papers
Minimal Embodiment Enables Efficient Learning of Number Concepts in Robot
Zhegong Shangguan, Alessandro Di Nuovo, Angelo Cangelosi
Robots are increasingly entering human-interactive scenarios that require understanding of quantity. How intelligent systems acquire abstract numerical concepts from sensorimotor e…
Supervised learning of spatial features with STDP and homeostasis using Spiking Neural Networks on SpiNNaker
Sergio Davies, Andrew Gait, Andrew Rowley +1
Artificial Neural Networks (ANN) have gained significant popularity thanks to their ability to learn using the well-known backpropagation algorithm. Conversely, Spiking Neural Netw…
Energy Efficient Personalized Hand-Gesture Recognition with Neuromorphic Computing
Muhammad Aitsam, Alessandro Di Nuovo
Hand gestures are a form of non-verbal communication that is used in social interaction and it is therefore required for more natural human-robot interaction. Neuromorphic (brain-i…
A Developmental Neuro-Robotics Approach for Boosting the Recognition of Handwritten Digits
Alessandro Di Nuovo
Developmental psychology and neuroimaging research identified a close link between numbers and fingers, which can boost the initial number knowledge in children. Recent evidence sh…
A Deep Neural Network for Finger Counting and Numerosity Estimation
Leszek Pecyna, Angelo Cangelosi, Alessandro Di Nuovo
In this paper, we present neuro-robotics models with a deep artificial neural network capable of generating finger counting positions and number estimation. We first train the mode…