44 citations · 226 across the 30 of their papers we have counts for
7 papers · 1 filter
Self-awareness in intelligent vehicles: Feature based dynamic Bayesian models for abnormality detection
Divya Thekke Kanapram, Pablo Marin-Plaza, Lucio Marcenaro +3
The evolution of Intelligent Transportation Systems in recent times necessitates the development of self-awareness in agents. Before the intensive use of Machine Learning, the dete…
Self-awareness in Intelligent Vehicles: Experience Based Abnormality Detection
Divya Kanapram, Pablo Marin-Plaza, Lucio Marcenaro +3
The evolution of Intelligent Transportation System in recent times necessitates the development of self-driving agents: the self-awareness consciousness. This paper aims to introdu…
Collective Awareness for Abnormality Detection in Connected Autonomous Vehicles
Divya Thekke Kanapram, Fabio Patrone, Pablo Marin-Plaza +5
The advancements in connected and autonomous vehicles in these times demand the availability of tools providing the agents with the capability to be aware and predict their own sta…
Dynamic Bayesian Approach for decision-making in Ego-Things
Divya Kanapram, Damian Campo, Mohamad Baydoun +4
This paper presents a novel approach to detect abnormalities in dynamic systems based on multisensory data and feature selection. The proposed method produces multiple inference mo…
Continual Learning of Predictive Models in Video Sequences via Variational Autoencoders
Damian Campo, Giulia Slavic, Mohamad Baydoun +2
This paper proposes a method for performing continual learning of predictive models that facilitate the inference of future frames in video sequences. For a first given experience,…
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…