Reinforcement & transfer learning based food quality analysis for defect detection - ON-954
Project type: ResearchDesired discipline(s): Engineering - computer / electrical, Engineering, Computer science, Mathematical Sciences
Company: Anonymous
Project Length: 4 to 6 months
Preferred start date: As soon as possible.
Language requirement: English
Location(s): Stoney Creek, ON, Canada; Halifax, NS, Canada; Toronto, ON, Canada
No. of positions: 1
Desired education level: Postdoctoral fellowRecent graduate
Open to applicants registered at an institution outside of Canada: Yes
About the company:
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.
Describe the project.:
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.
Required expertise/skills:
Reinforcement Learning, Machine Learning, Computer Vision
