Varietal classification of rice seeds using RGB and hyperspectral images

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  Fostering Precision Agriculture and Livestock Farming through Secure Access to Large-Scale HPC-Enabled Virtual Industrial Experimentation Environment Empowering Scalable Big Data Analytics (H2020-ICT-2018-2020) (CYBELE)

  Tachtatzis, C. (Principal Investigator), Cardona Amengual, J. (Academic), Andonovic, I. (Co-investigator), Atkinson, R. (Co-investigator) & Michie, C. (Co-investigator)

  European Commission - Horizon Europe + H2020

  1/01/19 → 31/12/21

  Project: Research

  • Satellite Image 100%
  • Image Inpainting 80%
  • Models 73%
  • Classification 60%
  • Image 43%

• Automatic Rice Seed Inspection Using Hyper-Spectral Imaging (Newton Fund)

  Tachtatzis, C. (Principal Investigator), Harle, D. (Co-investigator), Marshall, S. (Co-investigator) & Murray, P. (Co-investigator)

  Royal Academy of Engineering RAE

  15/11/15 → 14/02/17

  Project: Research

  • Hyperspectral Imaging 100%
  • Classifier 85%
  • Classification 85%
  • Spectral Feature 71%
  • Hyperspectral Image 64%