MinneApple
University of Minnesota, Data Repository for the University of Minnesota
Before trusting an AI system on a farming or food task you need a way to check it. Fruit detection, segmentation and counting in apple orchards using over 40,000 annotated instances and a separate test set.
QUICK INFO
SOLUTION TYPE
Models, data & tools
TECHNOLOGY CATEGORY
Benchmarks & evaluations
AREA OF WORK
Research & scientific knowledge
ACCESS
Free
DEPLOYMENT
Self-hosted / on-premise · Downloadable
SOURCE REVIEWED
August 17, 2026
What it helps with
- Count apples in an orchard photo
- Detect fruit on apple trees
- Estimate apple numbers from images
- Test a fruit detection model
- Annotated apple orchard images to download
Scope & audience
WHO IT'S FOR
Scientist / researcher · Developer / AI builder
AREA OF WORK
Research & scientific knowledge
COMMODITY / SCOPE
Cross-commodity
Access & technical details
ACCESS
Anyone can get it
INTERFACE
Dataset download
DEPLOYMENT
You run it yourself
LANGUAGES
Not stated by provider
Featured media
Source information
This listing was compiled from publicly available source material. Verify current details with the provider.
PROVIDER DOCUMENTATION
Reviewed August 2026
Explore more like this
ftw-tools
Fields of The World
Models, data & tools
Getting boundary data downloaded, models trained and outputs turned into map shapes involves a lot of glue code. This is an installable command line tool and code library covering those steps for one open field boundary project.
Free
Self-hosted / on-premise · Downloadable
Benchmarks & evaluations
ftw-tools
monitor-land-climate-sustainability
geospatial-imagery-and-remote-sensing
buildable-or-downloadable-component
benchmarks-and-evals
Free
Self-hosted / on-premise · Downloadable
August 23, 2026
- Download field boundary data from the command line
- Train a field boundary model
- Turn model output into map shapes
- Code library for field boundary work
- Command line tools for farm boundary work
AI model evaluation and verification
RISE Research Institutes of Sweden, via agrifoodTEF
Services & solution providers
Before trusting an AI system on a farming or food task you need a way to check it. Evaluates AI system performance and formally verifies safety requirements and EU AI Act compliance, focusing on robotic and drone control systems.
Paid or approval
Cloud-hosted
Benchmarks & evaluations
AI model evaluation and verification
research-develop
research-and-scientific-knowledge
obtainable-service-or-consultancy
benchmarks-and-evals
Paid or approval
Cloud-hosted
August 17, 2026
- Get an AI system evaluated for safety
- Check EU AI Act compliance for a farm robot
- Verify drone control software requirements
- Independent evaluation of robot control systems
- Formal safety verification for farm machinery
Is this your Resource?
Contact us to claim this listing and add details, screenshots or a demo.