Industries
Powering Computer Vision for Agriculture
Elevate agricultural growth, productivity, and sustainability through high-quality training and validation data, reducing waste and cost. Explore how computer vision in agriculture creates better results for AgTech companies like yours!
25% of Fortune 50 companies trust Sama to help them deliver industry-leading ML models
How Computer Vision Is Helpful in Agriculture?
Crop damage due to poor livestock health, poor yield due to changing weather conditions, inadequate soil quality, and external risks can all contribute to adversely impacting an agriculture business. This is where Sama’s computer vision algorithms step in as game changers.
By analyzing images and videos, our systems detect crop diseases, assess soil health, and monitor growth, enabling farmers to intervene timely. This helps us minimize resource wastage and maximize crop yields.
In the agricultural sector, computer vision technology can be a vital tool for ensuring desired results.
Use Cases
Computer Vision Solutions for Precision Agriculture & Food
Agtech doesn’t use only drones to capture images but also cameras, mobile phones; satellites; sensors etc to monitor crop health, detect diseases, pests, or weeds early on to minimize crop damage and maximize yield.
- Precision herbicide application to weeds, reducing chemical waste, costs and protecting crops
- Gauge crop heath by managing plant stress, disease or pests
- Precision irrigation reduces water waste and conserves resources
- Manage weed-related concerns with smart farming practices
Understand the health, behavior, and well-being of livestock with computer vision insights. habits, or identify signs of distress, enabling early intervention and improved animal management.
- Track movement patterns to detect anomalies
- Monitor feeding habits
- Identify early signs of distress for immediate intervention
- Make suitable livestock health decisions right on time
Enable autonomous harvesting to identify ripe fruits or vegetables and perform accurate harvesting to reduce labor-intensive tasks, improve efficiency, and minimize product damage.
- Auto-sort produce of different shapes and sizes to improve efficiencies and save costs
- Identify ripe fruits or vegetables to determine optimal picking points
- Identify poor quality crops or foreign materials for improved quality assurance
- Regularly optimize the farming procedure for better yield
Get better visibility into food waste streams with data-driven insights to reduce food waste, save costs and have a positive impact on the environment.
- Identify which foods are wasting most often, in order to better manage budgets and waste levels
- Reduce food waste and conserve costs with less food going to landfills
- Better management of resources, getting the best value against money
- Promote sustainability by reducing the environmental impact
Sama Annotation Solutions For AgTech
Sama Annotate
Image Annotation
Highly accurate image analysis allows you to prevent and control crop diseases to produce high-quality and pollution-free agricultural products while achieving high yields. Automatic grading and quality inspection of agricultural products also help you better improve the economic benefits of your products. This is how computer vision in the agriculture industry promotes smart farming.
Sama Annotate
Video Annotation
Advanced video annotation tools with complex object tracking for automated management of modern farms, livestock farming, automatic crop harvesting, and more. This makes crop management, maintenance, and storage easier. Optimize crop management models with high quality video annotations.
Sama Annotate
3D LiDAR & Radar
High-quality 3D training data at scale for a wide range of use cases, like monitoring the health of crops or checking soil conditions through geo-sensing and visual sensing. Incorporation of 3D LiDAR and Radar technologies can help farming business managers secure higher crop yields without spending on additional resources.
The Future of Computer Vision Applications in Agriculture
Technologies are evolving and influencing all industries and sectors. Similarly, computer vision applications are starting to revolutionize the agriculture sector, and Sama’s cutting-edge annotation for computer vision solutions are helping agricultural businesses join the ride.
By harnessing the power of artificial intelligence, deep learning, and machine learning technologies, farmers and businesses in the agriculture industry can optimize crop management and precision agriculture through crop monitoring and yield estimation and boost crop growth and crop yield.
From detecting livestock health to monitoring soil conditions with remarkable accuracy, our computer vision systems do it all. This information helps us increase crop yields, contribute to sustainability, and ensure food security.
For more details about our precision agriculture solutions and computer vision systems, contact us or request a callback!
Case Studies
High quality and accurate annotation solutions for the most complex
Agriculture & Food ML Models.
Sama Annotation Solution Trains AI Drones in Agriculture
Precision AI is disrupting the agricultural industry by training drones to recognize plant variations. Sama consistently delivers an accuracy rate of 99%.
Sama’s Annotation Solution Helps Restaurants Reduce Food Waste by 70%
Orbisk required labeling hundreds of thousands of accurate, high-quality training data (food images). Sama delivered expert annotation quality at scale. And working with Sama helped Orbisk guarantee their ethical AI supply chain.
Reduce the Risk of AI Model Failure due to Bad Data
Sama Delivers Quality at Scale
Our secure data annotation platform combined with our human-in-the-loop
experts make it easy to manage your training data pipeline at scale.
AgTech Experts
Our data experts have Identified anomalies, pests, and diseases in plants for >2000 anomalies against 2-3 hr SLA globally for over a decade.
Quality
No matter how complex your AgTech workflows, as you scale, Sama consistently delivers 99% acceptance rate, even with high ambiguity of images and prevalence of edge cases.
Scale
Scalable, proprietary ML-assisted annotation technology allows for higher accuracy and 3x increased efficiency as our workforce annotates millions of tasks per month.
