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POLENET

Automatic pollen analysis using convolutional neural networks: application to single-flower honey sorting.

Field
National
Date
31/05/2020 - 31/05/2023
Industry
  • Feeding
Budget
Funded by

Ministry of Economic Affairs and Digital Transformation, MINECO.

Website
Video

PROJECT INFORMATION

DESCRIPTION

Classify honey varieties more quickly, create pollen-related allergy maps or even determine the location of a crime. These are some of the applications of the artificial intelligence system for pollen counting being developed by researchers from the Computer Vision Area of the ai2 Institute, in collaboration with the staff of the Institute of Food Engineering for Development of the UPV. The ultimate goal is to have an application that helps laboratory technicians to identify pollens, standardizing classification criteria, thus being able to perform the analysis on many more samples and obtaining, therefore, faster and more objective results.

Classify honey varieties more quickly, create pollen-related allergy maps or even determine the location of a crime. These are some of the applications of the artificial intelligence system for pollen counting being developed by researchers from the Computer Vision Area of the ai2 Institute, in collaboration with the staff of the Institute of Food Engineering for Development of the UPV. The ultimate goal is to have an application that helps laboratory technicians to identify pollens, standardizing classification criteria, thus being able to perform the analysis on many more samples and obtaining, therefore, faster and more objective results.

Contact information

Valiente González, José Miguel
University Professor - PDI

Ai2

Technological capabilities

IA
Artificial Vision