Dr. Swati Shrestha
Weed Science lab at Oklahoma State University is seeking a motivated PhD student to work on an exciting project focused on automated grassweed detection in wheat fields.
Project Description:
Despite the increasing use of Unmanned Aerial Systems (UAS) in precision agriculture, efficiently processing high-resolution imagery data to distinguish between crops and weeds remains a significant challenge. Traditional machine learning methods rely on rule-based knowledge and shallow image features, resulting in labor-intensive processes and limited effectiveness. In contrast, deep learning offers the potential for extracting rich feature representations directly from large datasets, leading to higher performance and more robust models.
Your Role:
As a PhD student on this project, you will be at the forefront of developing robust deep learning models using RGB and multispectral imagery for early-stage grassweed detection in wheat fields. You will have the opportunity to leverage cutting-edge techniques in machine learning and computer vision to address real-world challenges in precision agriculture.
Requirements:
- A strong background in computer science, engineering, or a related field
- Experience or interest in machine learning, computer vision, and/or agricultural technology
- Proficiency in programming languages such as Python and R
- Excellent analytical and problem-solving skills
- Ability to work independently and collaborate effectively within a multidisciplinary tea
How to apply:
Interested candidate should email their CV and cover letter to swati.shrestha@okstate.edu
