Publications

• Article dans une revue

Statistical Analysis of Measurement Processes Using Multi-Physic Instruments: Insights from Stitched Maps

Clement Moreau, Julie Lemesle, David Páez Margarit, François Blateyron, Maxence Bigerelle

Metrology, 2024, 4, pp.141 - 163. ⟨10.3390/metrology4020010⟩. ⟨hal-04544819⟩

• Poster de conférence

Appoutchou

Soilio Coulibaly

Mardi des chercheurs, Mar 2024, MONS, Belgique. ⟨hal-04511351⟩

• Poster de conférence

Enhancing the memorization of tactical soccer scenes: Investigating the role of drawing according to visuospatial abilities

Sabrine Tlili, Hatem Ben Mahfoudh, Bachir Zoudji

This study investigates the impact of drawing on the memorization of soccer tactical scenes, considering visuospatial abilities (VSA). Fifty-four novice male players were randomly assigned to two conditions: a control condition (pre-drawn diagrams with oral explanation) and an experimental…

Mardi des Chercheurs, Mar 2024, Mons, Belgium. ⟨hal-04598398⟩

• Poster de conférence

Génération volontaire déclassé

Vincent Delcorte

La Première Guerre mondiale aura laissé en France un trou béant. Vide générationnel creusée dans celui des tranchées. Dans les années 1920 et 1930, les jeunes intellectuels français sont précipités en politique par les conséquences de la guerre : diplomatie incertaine, économie en faillite,…

Mardi des Chercheurs 2024, Mar 2024, Mons, Belgique. ⟨hal-04525097⟩

• Poster de conférence

«Methodologies For Demand Forecasting in supply chain: A Systematic Literature Review And Bibliographic Analysis»

Nguyen Thanh Tuan, Bekrar Abdelghani, Le Thi Muoi, Artiba Abdelhakim, Chargui Tarik

Mardi de Chercheurs, Mar 2024, Mons, Belgium. 2024. ⟨hal-04542842⟩

• Poster de conférence

Leveraging Efficient Models for Recognizing Drivers' Facial Expressions

Ibtissam Saadi, Douglas W Cunningham, Abdelmalik Taleb-Ahmed, Abdenour Hadid, Yassin El Hillali

Our new approach, ShuffViT-DFER, combines lightweight CNN and vision transformer models for efficient and accurate real-time driver facial expression recognition. By merging their features effectively, we outperform existing methods on benchmark datasets like KMU-FED and KDEF.

Mardi des chercheurs 2024, Mar 2024, mons, Belgium. ⟨hal-04546700⟩

• Poster de conférence

Expert and Machine Digital Twins for Nuclear Systems Analysis, Jumeaux Numériques Machine et Expert pour l'Analyse de Systèmes Nucléaires

Corentin Ascone, Frédéric Vanderhaegen, Benjamin Verhaeghe

The thesis aims to assist experts in their process of Reactor Coolant Pump (RCP) analysis. The idea is to design both Expert and RCP Digital Twins to access easily and at any time to precious informations. Then we design EXPERIA, an application to assist experts in their activities of expertise.…

Mardi des Chercheurs 2024, Mar 2024, Mons, Belgium. , 2024. ⟨hal-04542473⟩

• Poster de conférence

Marceline Desbordes-Valmore voyageuse, Marceline Desbordes-Valmore, the sad wanderer

Maxance Lardjane

Ce poster, établi dans le cadre du Mardi des Chercheurs de l'Université de Mons, montre une dimension très importante de Marceline Desbordes-Valmore, qui est son appétance contrainte au voyage. Dans une errance subie, qu'elle soit pour chercher en Guadeloupe un oncle fortuné, pour trouver…, This poster, done as an entry for UMONS' "Mardi des Chercheurs" edition of 2024, shows a very important aspect of Marceline Desbordes-Valmore's life : her not-so-desired wanderlust. Marceline's life was marked by wandering, whether in search of a wealthy uncle in Guadeloupe…

Mardi des Chercheurs 2024, Mar 2024, Mons, France. ⟨hal-04524235⟩

• Poster de conférence

Espace et mobilier liturgiques de la cathédrale Notre Dame de Tournai, 1566 - 1792. Essai de reconstitution et interprétation

Tiphanie TT Torres

Mardi des Chercheurs, Mar 2024, Mons, Belgique. ⟨hal-04542427⟩

• Poster de conférence

Leveraging Efficient Models for Recognizing Drivers' Facial Expressions

Ibtissam Saadi, Douglas W Cunningham, Abdelmalik Taleb-Ahmed, Abdenour Hadid, Yassin El Hillali

Our new approach, ShuffViT-DFER, combines lightweight CNN and vision transformer models for efficient and accurate real-time driver facial expression recognition. By merging their features effectively, we outperform existing methods on benchmark datasets like KMU-FED and KDEF.

Mardi des chercheurs 2024, Mar 2024, mons, Belgium. ⟨hal-04985694⟩