Offre en lien avec l’Action/le Réseau : – — –/– — –

Laboratoire/Entreprise : LITIS Lab (INSA Rouen Normandy) and University of
Durée : 4 years
Contact : paul.honeine@univ-rouen.fr
Date limite de publication : 2023-05-15

Contexte :
Cotutelle INSA Rouen Normandy and University of Tartu (Estonia)

Supervisors: Amnir Hadachi, Abdelaziz Bensrhair, Paul Honeine

Please send CV and transcripts to:
– Amnir Hadachi: hadachi@ut.ee
– Abdelaziz Bensrhair: abdelaziz.bensrhair@insa-rouen.fr
– Paul Honeine: paul.honeine@univ-rouen

Sujet :
In the last decades, we witnessed rapid artificial intelligence advancements built upon deep learning (DL). Moreover, the DL decision mechanism is so obscure that testing is the only way to verify it. Hence, the process from training to testing any model is computationally demanding. Consequently, due to their high carbon footprint, DL networks become a concern for suitability. From this perspective, green learning (GL) has been presented as a potential solution to address these concerns. Thus, the Ph.D. topic is focused on exploring the possibilities of the GL paradigm and how it can be adopted in rethinking and redesigning the models’ architectures to reduce the carbon footprint of computer vision algorithms based on Deep learning.

Profil du candidat :
The PhD candidate must be a graduate student or have a MSc or engineering degree in one of the following fields: computer science, data science, computer vision, applied mathematics or equivalent. She/he must have a strong background in machine learning and/or computer vision. Experience in deep learning is appreciated, as well as proficient programming skills in Python.

Formation et compétences requises :
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Adresse d’emploi :
INSA Rouen Normandy and University of Tartu (Estonia)