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Image classification based disease and pest detection in agriculture

  • Full or part time
  • Application Deadline
    Applications accepted all year round
  • Competition Funded PhD Project (Students Worldwide)
    Competition Funded PhD Project (Students Worldwide)

About This PhD Project

Project Description

Developing image clarification models using tools such as Google Tensorflow. The models need to be capable of identifying different diseases and insect infestations in specific crops such as cotton.

The project aims to develop various classifiers using machine learning approaches such as Convolutional neural networks (CNN). The key purpose is to accurately identify specific diseses and insect infestations in crop fields. The project may include image data collection using airborne vehicles (drones). The images may be both RGB and Hyperspectral images. The models are expected to develop early infestaion detection capabilities so that farmers can take timely remedial actions to reduce loss and improve productivity. The ideal candidate would have strong computing and mathematical backgrounds with excellent programming skills. Expertise in ML, classification, image processing, Python, Tensorlow would be a plus.

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