Reinforcement & transfer learning based food quality analysis for defect detection - ON-954

Genre de projet: Recherche
Discipline(s) souhaitée(s): Génie - informatique / électrique, Génie, Informatique, Sciences mathématiques
Entreprise: Anonymous
Durée du projet: 4 à 6 mois
Date souhaitée de début: Dès que possible
Langue exigée: Anglais
Emplacement(s): Stoney Creek, ON, Canada; Halifax, NS, Canada; Toronto, ON, Canada
Nombre de postes: 1
Niveau de scolarité désiré: Recherche postdoctoraleNouvelle diplômée/nouveau diplômé
Ouvert aux candidatures de personnes inscrites à un établissement à l’extérieur du Canada: Yes

Au sujet de l’entreprise: 

A multinational food technology company with headquarters in Stoney Creek, Ontraio. The company provides AI powered technology for companies across the food and agriculture supply chain.

Veuillez décrire le projet.: 

The company wants to leverage the capabilities of reinforcement and transfer learnings to establish a robust analytical framework. This framework aims to discern various types of defects and anomalies present in diverse food categories.

The project will involve the commercial deployment of advanced reinforcement and transfer learning methodologies alongside the integration of the latest research within this domain. The ultimate objective is to develop a sophisticated, data-driven system that enhances the precision and reliability of quality control mechanisms in the food industry.

Through this initiative, the company anticipates setting new standards for food safety and quality assurance, bolstering its position at the forefront of technological innovation in the Food & Ag industry.

Expertise ou compétences exigées: 

Reinforcement Learning, Machine Learning, Computer Vision