Validation of Yield Estimation based on Computer Vision

Automated yield estimation using Artificial Intelligence to images and videos of fruit trees.

Interested in this service? Contact us at roberto.garcia[at]udl.cat 

Overview

The service offers validation of fruit detections, diameter estimation and yield estimates using AI, in particular Computer Vision techniques. 

We help solution providers to check the solutions performance using reference datasets or experiments conducted in testing fields. The service might also include the generation of reference datasets and expected detection, diameter measures or yield values, which can be used both for validation and training of the AI solution based on Computer Vision. 

More about the service

Discover more about our service, including how it can benefit you, the delivery process, and the options for customisation tailored to your specific needs!

The service helps solution providers to validate the accuracy of their yield estimations, fruit detection and diameter estimation using AI and Computer Vision techniques, ensuring reliable performance through reference datasets and testing.

The validation service will be conducted in designated testing fields or at your location, depending on availability and requirements. The execution of the service will take up to two weeks, allowing time for data collection and analysis. You will receive a comprehensive report detailing the validation results, including metrics on fruit detection accuracy, diameter estimation, and overall yield estimates. Additionally, metadata related to environmental conditions during testing will be provided. To facilitate this service, customers will need to supply access to relevant images or videos of fruit trees, as well as any specific criteria or parameters for the validation process. This service can be delivered year-round, although timing may be influenced by the fruiting cycle of the trees being assessed.

The service can be customised for your specific product.
Location
Spain
At user's premises
Remote
Type of Sector
Greenhouse
Horticulture
Tree Crops
Viticulture
Type of service
AI model training
Collection of test data
Performance evaluation
Test design
Test setup
Test execution
Accepted type of products
Data
Software or AI model

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