Hyperspectral image classification for quality control in agri-food sector

Deep Learning applied to seed classification

Client
Iris Technology
Sector
Computer Vision
Service
Method
deep learning
More information

Use case

The client, a R&D company with high expertise in hyperspectral imaging, wanted an assessment to build an end-to-end device to automatically estimate defects of food products from a sample, under certain specifications

Solution

We provided an initial training on Deep Learning to update client team with the required skills to start exploring solution for their current problem.

The assessment consisted of regular meetings with the client to iteratively build an image classification solution, including different items: computer hardware definition and setup, object segmentation, anomaly detection, and object classification.

Would you like to receive more information about 
any of the projects?

More Cases

Method: Simulation and optimization
Marcelus Fabri, Helena Ramalhinho
Logistics optimization
Method: Word embeddings, Spectral clustering
Joan Verdú, Nandan Rao, Omiros Papaspiliopoulos
Analysis of tweets to understand main topics and triggering events, together with tweet toxicity
Method: Optimization
Jésica de Armas, Helena Ramalhinho
Crew optimization

How we can help

Let us train you to acquire those data science analytics skills that you or your team are missing.

Need some help in any analytics challenge you are facing? Get your analytics to the next level: count on us as expert consultants!

Contact us

We’d love to hear from you… Drop us a line to get in touch!

More informacion about this case study

You can ask us for more information about this case study. Leave us your email and you will recieve all the information.