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Using deep learning for weed detection

Although the deep learning area has made a major breakthrough in the latest developments, there are still numerous challenges that have to be resolved when working with real-world data. In this particular case, we are working with real-world data to detect and classify weeds. You will explore the neural network architectures, augmentation techniques, and techniques to reduce the computational time while maintaining the overall system performance.

The research will be undertaken using publicly available data as well as real-world data. The model will implement industry standard design principles and UK design standards to ensure that the designs are safe and efficient.

This project is a based at the AI: Social and Digital Innovation Centre. The researcher will become part of an established and high-energy research group which meets frequently and works collaboratively on a range of industry problems across numerous industries.

Due to the technical nature of this project, the ideal candidate will either be a computer science or computer system engineering graduate with a programming background. A Masters’ degree is desired but not essential for the role.

Doctoral research programmes (PhDs) take a proud place in the world-class research environment and community at Brunel.

PhD students are recognised and valued by their supervisors as an essential part of their departments and a key component of the university's overall strategy to develop and deliver world-class research. A PhD programme is expected to take 3 years full-time or 6 years part-time, with intakes starting in January, April or October.

The general University entrance requirement for registration for a research degree is normally a First or Upper Second Class Honours degree (1st or 2:1) or an international equivalent. A Masters degree is a welcome, but not required, qualification for entry. 

How to apply

If you are interested in applying for the above PhD topic please follow the steps below:

  1. Contact the supervisor by email or phone to discuss your interest and find out if you woold be suitable. Supervisor details can be found on this topic page. The supervisor will guide you in developing the topic-specific research proposal, which will form part of your application.
  2. Click on the 'Apply here' button on this page and you will be taken to the relevant PhD course page, where you can apply using an online application.
  3. Complete the online application indicating your selected supervisor and include the research proposal for the topic you have selected.

Good luck!

This is a self funded topic

Brunel offers a number of funding options to research students that help cover the cost of their tuition fees, contribute to living expenses or both. See more information here: https://www.brunel.ac.uk/research/Research-degrees/Research-degree-funding. The UK Government is also offering Doctoral Student Loans for eligible students, and there is some funding available through the Research Councils. Many of our international students benefit from funding provided by their governments or employers. Brunel alumni enjoy tuition fee discounts of 15%.

Meet the Supervisor(s)


Tatiana Kalganova -

DEGREES AWARDED

  • PhD Napier University
  • Research-engineer degree Belarusian State University of Informatics and Radio-electronics, Minsk, Belarus
  • MSc (distinction) Belarusian State University of Informatics and Radio-electronics, Minsk, Belarus

ACADEMIC POSTS

  • 2000-present Lecturer Brunel University London
  • 2003-2011 Business Fellow London Technology Network, LTN Link between research activities at Brunel University London and industry
  • 1997-2000 PhD student Napier University
  • 1994-1997 Research Assistant Belarusian State University of Informatics and Radio-electronics