Computer vision for fruits and vegetables sorting and classification- QC-321

Desired discipline(s): Engineering - computer / electrical, Engineering, Computer science, Mathematical Sciences
Company: TrIAmec Inc
Project Length: 4 to 6 months
Preferred start date: 08/21/2020
Language requirement: Flexible
Location(s): Montreal, QC, Canada; Canada
No. of positions: 1
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About the company: 

At TrIAmec, our objective is to help farmers produce more and better. Our solution is to develop a versatile machine to help farmers depends less on foreign workers. It is particularly important also in time of crisis like the one we are living in the present times when it is hard for farmers to get foreign workers to come work for them. Due to the current pandemic their number has decreased.

Please describe the project.: 

For our solution, we are using a Convolutional neural network to classify and sort tomatoes. This summer we concentrated on the tomato software. Our main objective is to build our database this summer mid or end-july. The researcher would help us improve and optimize our software and choose the best hardware for our problem. If the time allows for it- the same software could be applied and developed for cucumber and bell peppers.

Required expertise/skills: 

We are looking for a candidate with:

  • Knowledge in machine learning, Deep-learning, Convolutional neural network, python, C, C++, computer vision
  • Knowledge in agricultural machinery field and in computer vision for sorting and classify is an asset.