output
20202024
most citedSolitary-wave loads on a three-dimensional submerged horizontal plate: Numerical computations and comparison with experiments

30 citations

Showing 2024Show all

11 papers · 1 filter

cs.CL2024

Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering

Imed Keraghel, Mohamed Nadif

Recent advances in machine learning, particularly Large Language Models (LLMs) such as BERT and GPT, provide rich contextual embeddings that improve text representation. However, c…

cs.AI2024

A Pre-Trained Graph-Based Model for Adaptive Sequencing of Educational Documents

Jean Vassoyan, Anan Schütt, Jill-Jênn Vie +3

Massive Open Online Courses (MOOCs) have greatly contributed to making education more accessible. However, many MOOCs maintain a rigid, one-size-fits-all structure that fails to ad…

cs.CV2024

Evolution of Detection Performance throughout the Online Lifespan of Synthetic Images

Dimitrios Karageorgiou, Quentin Bammey, Valentin Porcellini +3

Synthetic images disseminated online significantly differ from those used during the training and evaluation of the state-of-the-art detectors. In this work, we analyze the perform…

eess.IV20245 cited

How to Best Combine Demosaicing and Denoising?

Yu Guo, Qiyu Jin, Jean-Michel Morel +1

Image demosaicing and denoising play a critical role in the raw imaging pipeline. These processes have often been treated as independent, without considering their interactions. In…

math.DG2024

The graded group action framework for sub-riemannian orbit models in shape spaces

Thomas Pierron, Alain Trouvé

In the standard orbit model on shape analysis, a group of diffeomorphism on the ambient space equipped with a right invariant sub-riemannian metric acts on a space of shapes and in…

eess.IV202429 cited

Fast, nonlocal and neural: a lightweight high quality solution to image denoising

Yu Guo, Axel Davy, Gabriele Facciolo +2

With the widespread application of convolutional neural networks (CNNs), the traditional model based denoising algorithms are now outperformed. However, CNNs face two problems. Fir…