20 citations · 20 across the 1 of their papers we have counts for
5 papers
Learning Self-Awareness for Autonomous Vehicles: Exploring Multisensory Incremental Models
Mahdyar Ravanbakhsh, Mohamad Baydoun, Damian Campo +4
The technology for autonomous vehicles is close to replacing human drivers by artificial systems endowed with high-level decision-making capabilities. In this regard, systems must…
Anomaly Detection in Video Data Based on Probabilistic Latent Space Models
Giulia Slavic, Damian Campo, Mohamad Baydoun +4
This paper proposes a method for detecting anomalies in video data. A Variational Autoencoder (VAE) is used for reducing the dimensionality of video frames, generating latent space…
Hierarchy of GANs for learning embodied self-awareness model
Mahdyar Ravanbakhsh, Mohamad Baydoun, Damian Campo +4
In recent years several architectures have been proposed to learn embodied agents complex self-awareness models. In this paper, dynamic incremental self-awareness (SA) models are p…
Learning Multi-Modal Self-Awareness Models for Autonomous Vehicles from Human Driving
Mahdyar Ravanbakhsh, Mohamad Baydoun, Damian Campo +4
This paper presents a novel approach for learning self-awareness models for autonomous vehicles. The proposed technique is based on the availability of synchronized multi-sensor dy…
A Multi-perspective Approach To Anomaly Detection For Self-aware Embodied Agents
Mohamad Baydoun, Mahdyar Ravanbakhsh, Damian Campo +5
This paper focuses on multi-sensor anomaly detection for moving cognitive agents using both external and private first-person visual observations. Both observation types are used t…