SustainBench
Stanford Sustainability and Artificial Intelligence Lab
Before trusting an AI system on a farming or food task you need a way to check it. Crop type mapping, crop yield prediction, field delineation and cropland segmentation tasks with PyTorch dataloaders and baseline models.
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
- Map crop types from satellite imagery
- Predict crop yield from data
- Draw field boundaries automatically
- Test models on cropland mapping
- Ready made data loaders and baselines
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
Code repository
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
MinneApple
University of Minnesota, Data Repository for the University of Minnesota
Models, data & tools
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.
Free
Self-hosted / on-premise · Downloadable
Benchmarks & evaluations
MinneApple
research-develop
research-and-scientific-knowledge
buildable-or-downloadable-component
benchmarks-and-evals
Free
Self-hosted / on-premise · Downloadable
August 17, 2026
- 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
Global Safety Evaluation for Autonomous Robots
INRAE, via agrifoodTEF
Services & solution providers
Before trusting an AI system on a farming or food task you need a way to check it. Reviews risk assessment, safety function design and validation plans of autonomous farm robots against ISO 18497, ISO 25119 and Machinery Regulation 2023/1230.
Paid or approval
Cloud-hosted
Benchmarks & evaluations
Global Safety Evaluation for Autonomous Robots
research-develop
research-and-scientific-knowledge
obtainable-service-or-consultancy
benchmarks-and-evals
Paid or approval
Cloud-hosted
August 17, 2026
- Review my farm robot safety design
- Check a risk assessment for an autonomous machine
- Does my robot meet machinery rules
- Validate safety functions on farm robots
- Safety review against farm machinery standards
Is this your Resource?
Contact us to claim this listing and add details, screenshots or a demo.