Artificial Intelligence And Machine Learning In Agriculture Today
Although they promise streamlined farming operations, higher yields and greater costs savings for growers, how much of AI and machine learning in agriculture today is more hype than reality?
NEW FACIAL RECOGNITION FEATURE LAUNCHED BY CONSUS FRESH
Consus has developed an intelligent software-based system that reduces the burden of audits and improves productivity. By linking HR records to labour deployment the facial recognition module enables accurate costing of all products and improved traceability.
Plant Breeders Tap Robots, Drones and AI to Feed the World
Plant breeding has been going on for 10,000 years but technology -unmanned aerial vehicles (UAVs), robots, artificial intelligence (AI) and machine learning -is revolutionizing the practice.
Artificial Intelligence And Its Uses In Ag Irrigation
Do you have a problem that AI might be able to solve? If so, have you started collecting the data that might be needed? The sooner you get started, the sooner you might be able to see the benefits.
Artificial Intelligence is the Latest Greenhouse Automation Technology
For instance, our greenhouse clients can obtain a 50% to 70% reduction in error in harvest forecasts from the start; following a year of further learning, the AI technology can reduce errors by more than 70%.
More Accurately Forecasting Future Harvests Using Artificial Intelligence
Using Motorleafs artificial intelligence and machine-learning algorithms, the digital agronomist software can acquire data from indoor growing conditions. In turn, the algorithms learn growing patterns in the greenhouse, which then can predict the size of future harvests.
C2-A2 AGRODROID - world's new Smart Farming product
European software developer 'Cognitive Technologies has developed the world's first industrial agrodroid for international agricultural market.
Artificial Intelligence in Agriculture: Understanding Crop Growth
There are many different types of potential applications of AI in agriculture -- ranging from machine control, to image analysis, to improving our understanding of where, when, and how a crop might respond toparticular environmental conditions.
Some Deep Learnings from Applying Deep Learning
To build a robust deep learning model, it can be much more than training or fine tuning some existing models (e.g. inception v3, resnet, LSTM, etc.) with your own dataset. These winning models are your best friend and can usually serve as base models.
It is Agriculture's Turn to Put the Next Generation of Digital Technologies to Work
It is exciting to see the technologies that have made a life-saving difference in medicine now being applied to producing more food from every acre with the best quality.
A Tale of Two Sciences-Artificial Intelligence Meets Agronomy
If 29-year-old me were here in the present day looking at whats going on in agriculture, I cant help but wonder what would be going through my mind-"Do I believe what I am seeing?" or "Am I inside a Sci-Fi movie?"
Beyond the Hype: AI in Agtech
With Agrilyst, growers can understand which of their crops are the highest performers based on yield, growth rate, or both and run production scenarios with higher performers having more space allocation. These recommendations help growers optimize the space on their farm and drive significantly higher revenues.
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