Search Results for author:
Found 11 papers, 1 papers with code
Calibration of Vehicular Traffic Simulation Models by Local Optimization
We assess the proposed technique on a model of Brussels, Belgium, using data from real traffic monitoring devices.
HybridTrack: A Hybrid Approach for Robust Multi-Object Tracking
The evolution of Advanced Driver Assistance Systems (ADAS) has increased the need for robust and generalizable algorithms for multi-object tracking.
Strada-LLM: Graph LLM for traffic prediction
Furthermore, we adopt a lightweight approach for efficient domain adaptation when facing new data distributions in few-shot fashion.
Interpretable Deep Multimodal Image Super-Resolution
Multimodal image super-resolution (SR) is the reconstruction of a high resolution image given a low-resolution observation with the aid of another image modality.
Multimodal Deep Unfolding for Guided Image Super-Resolution
The deep unfolding architecture is used as a core component of a multimodal framework for guided image super-resolution.
Multimodal Image Super-resolution via Deep Unfolding with Side Information
Deep learning methods have been successfully applied to various computer vision tasks.
Twitter User Geolocation using Deep Multiview Learning
Predicting the geographical location of users on social networks like Twitter is an active research topic with plenty of methods proposed so far.
Multiview Deep Learning for Predicting Twitter Users' Location
In the context of Twitter user geolocation, we realize MENET with textual, network, and metadata features.
Multi-modal dictionary learning for image separation with application in art investigation
Our dictionary learning framework can be tailored both to a single- and a multi-scale framework, with the latter leading to a significant performance improvement.
X-ray image separation via coupled dictionary learning
In support of art investigation, we propose a new source sepa- ration method that unmixes a single X-ray scan acquired from double-sided paintings.
Bayesian crack detection in ultra high resolution multimodal images of paintings
The preservation of our cultural heritage is of paramount importance.
