5 citations · 12 across the 11 of their papers we have counts for
13 papers
Automatic Cause Determination in Road Scene Understanding Using Qualitative Reasoning and Four-Valued Logic
Nassim Belmecheri, Arnaud Gotlieb, Nadjib Lazaar +1
Road scene understanding in automated driving (AD) aims to build a comprehensive analysis of video sequences taken on the road by embedded or fixed cameras (e.g., mounted on vertic…
Boosting the Learning for Ranking Patterns
Nassim Belmecheri, Noureddine Aribi, Nadjib Lazaar +2
Pattern mining is a valuable tool for exploratory data analysis, but identifying relevant patterns for a specific user is challenging. Various interestingness mea- sures have been…
Learning Symbolic Constraint Representations from Examples: A Neuro-Symbolic Approach
Nassim Belmecheri, Arnaud Gotlieb, Nadjib Lazaar +1
Learning user-defined concepts as constraint networks has been extensively studied in the constraint acquisition (CA) literature. However, existing approaches typically rely on int…
Rashomon in the Streets: Explanation Ambiguity in Scene Understanding
Helge Spieker, Jørn Eirik Betten, Arnaud Gotlieb +2
Explainable AI (XAI) is essential for validating and trusting models in safety-critical applications like autonomous driving. However, the reliability of XAI is challenged by the R…
Metamorphic Testing of Multimodal Human Trajectory Prediction
Helge Spieker, Nadjib Lazaar, Arnaud Gotlieb +1
Context: Predicting human trajectories is crucial for the safety and reliability of autonomous systems, such as automated vehicles and mobile robots. However, rigorously testing th…
Prompting for Performance: Exploring LLMs for Configuring Software
Helge Spieker, Théo Matricon, Nassim Belmecheri +7
Software systems usually provide numerous configuration options that can affect performance metrics such as execution time, memory usage, binary size, or bitrate. On the one hand,…
Learning Graph Representation of Agent Diffusers
Youcef Djenouri, Nassim Belmecheri, Tomasz Michalak +3
Diffusion-based generative models have significantly advanced text-to-image synthesis, demonstrating impressive text comprehension and zero-shot generalization. These models refine…
Explainable Scene Understanding with Qualitative Representations and Graph Neural Networks
Nassim Belmecheri, Arnaud Gotlieb, Nadjib Lazaar +1
This paper investigates the integration of graph neural networks (GNNs) with Qualitative Explainable Graphs (QXGs) for scene understanding in automated driving. Scene understanding…
Evaluating Human Trajectory Prediction with Metamorphic Testing
Helge Spieker, Nassim Belmecheri, Arnaud Gotlieb +1
The prediction of human trajectories is important for planning in autonomous systems that act in the real world, e.g. automated driving or mobile robots. Human trajectory predictio…
Towards Trustworthy Automated Driving through Qualitative Scene Understanding and Explanations
Nassim Belmecheri, Arnaud Gotlieb, Nadjib Lazaar +1
Understanding driving scenes and communicating automated vehicle decisions are key requirements for trustworthy automated driving. In this article, we introduce the Qualitative Exp…
Trustworthy Automated Driving through Qualitative Scene Understanding and Explanations
Nassim Belmecheri, Arnaud Gotlieb, Nadjib Lazaar +1
We present the Qualitative Explainable Graph (QXG): a unified symbolic and qualitative representation for scene understanding in urban mobility. QXG enables the interpretation of a…
Acquiring Qualitative Explainable Graphs for Automated Driving Scene Interpretation
Nassim Belmecheri, Arnaud Gotlieb, Nadjib Lazaar +1
The future of automated driving (AD) is rooted in the development of robust, fair and explainable artificial intelligence methods. Upon request, automated vehicles must be able to…
Boosting the Learning for Ranking Patterns
Nassim Belmecheri, Noureddine Aribi, Nadjib Lazaar +2
Discovering relevant patterns for a particular user remains a challenging tasks in data mining. Several approaches have been proposed to learn user-specific pattern ranking functio…