Search Results for author:
Found 12 papers, 3 papers with code
Event-based Vision for Early Prediction of Manipulation Actions
In this study, we introduce an event-based dataset on fine-grained manipulation actions and perform an experimental study on the use of transformers for action prediction with events.
Reconfigurable Cyber-Physical System for Lifestyle Video-Monitoring via Deep Learning
Reconfiguration reduces up to 22% the local nodes energy consumption extending the device operating time, preserving similar accuracy with respect to the alternative with no reconfiguration.
Simulation, visualization and analysis tools for pattern recognition assessment with spiking neuronal networks
Computational modeling is becoming a widely used methodology in modern neuroscience.
Exploring vestibulo-ocular adaptation in a closed-loop neuro-robotic experiment using STDP. A simulation study
In this work, we use the Neuro-robotic Platform (NRP)to evaluate the vestibulo ocular cerebellar adaptatIon (Vestibulo-ocular reflex, VOR)mediated by two STDP mechanisms located at the cerebellar molecular layer and the vestibular nuclei respectively.
A Metric for Evaluating Neural Input Representation in Supervised Learning Networks
A Purkinje cell becomes sensitive to each neural input state and, consequently, the network operates as a function able to generate a desired output for each provided input by means of supervised learning.
VOR Adaptation on a Humanoid iCub Robot Using a Spiking Cerebellar Model
The spiking neural network computation, including event- and time-driven neural dynamics, neural activity, and spike-timing dependent plasticity (STDP) mechanisms, leads to a nondeterministic computation time caused by the neural activity volleys encountered during cerebellar simulation.
On robot compliance. A cerebellar control approach
The spiking cerebellar controller continuously adapts the torque commands provided to the robot from experience as STDP is deployed.
Real-time clustering and multi-target tracking using event-based sensors
The potential of our approach is demonstrated in a multi-target tracking application using Kalman filters to smooth the trajectories.
Joint direct estimation of 3D geometry and 3D motion using spatio temporal gradients
Conventional image motion based structure from motion methods first compute optical flow, then solve for the 3D motion parameters based on the epipolar constraint, and finally recover the 3D geometry of the scene.
Scalability in Neural Control of Musculoskeletal Robots
Anthropomimetic robots are robots that sense, behave, interact and feel like humans.
Real-time Model-based Articulated Object Pose Detection and Tracking with Variable Rigidity Constraints
A novel model-based approach is introduced for real-time detection and tracking of the pose of general articulated objects.
Real-Time Model-Based Rigid Object Pose Estimation and Tracking Combining Dense and Sparse Visual Cues
We propose a novel model-based method for estimating and tracking the six-degrees-of-freedom (6DOF) pose of rigid objects of arbitrary shapes in real-time.
