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Data Annotation Services for Smarter Agriculture
We provide training data for agriculture to teach your model to perform agriculture-related tasks, paving the way for automated farming of the future.
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We Scale Teams for:
Data Annotation for Agriculture Industry at Label Your Data
Data annotation for the agriculture industry implies labeling of images, videos, or sensor data with information such as crop types, disease detection, pest identification, growth stages, and yield estimation. Precise and comprehensive annotations facilitate the advancement of technologies in smart farming and precision agriculture.
Our skilled annotators at Label Your Data apply their domain knowledge to deliver quality and secure data annotation in farming. Additionally, we employ data labeling tools to ensure consistent and reliable results, providing our clients with custom training datasets to meet their agriculture data annotation needs.
On photo:
Olha, Karyna
Our Data Annotation Services for Agricultural Companies
The Label Your Data team is skilled in the most sought-after types of data annotation services in agriculture, as well as data processing services for the agribusinesses. Whether you require agriculture data annotation services or any other data processing services, our annotators are here to provide high-quality solutions tailored to your specific project needs for AI in farming.
Our clients mostly require labeled data for Computer Vision for their harvesting or crops selection projects. Hence, we tend to do:
Semantic Segmentation for Crop Monitoring
Image Categorization for Livestock Management
Bounding Boxes for Pest & Disease Detection
Polygonal Annotation for Field Mapping
Semantic segmentation helps your computer vision models accurately analyze and monitor different crop regions in images, enabling precise crop monitoring and targeted interventions.
With image categorization, your model can classify livestock images based on breeds, health conditions, or specific characteristics, supporting effective livestock management practices.
By employing bounding box annotation, the models can detect and localize pests, diseases, or symptoms in crops, facilitating early identification and targeted treatment.
Polygonal annotation enables AI to map and delineate specific field areas or boundaries, aiding in crop planning, resource allocation, and precision farming practices.
Semantic Segmentation for Crop Monitoring
Semantic segmentation helps your computer vision models accurately analyze and monitor different crop regions in images, enabling precise crop monitoring and targeted interventions.
Image Categorization for Livestock Management
With image categorization, your model can classify livestock images based on breeds, health conditions, or specific characteristics, supporting effective livestock management practices.
Bounding Boxes for Pest & Disease Detection
By employing bounding box annotation, the models can detect and localize pests, diseases, or symptoms in crops, facilitating early identification and targeted treatment.
Polygonal Annotation for Field Mapping
Polygonal annotation enables AI to map and delineate specific field areas or boundaries, aiding in crop planning, resource allocation, and precision farming practices.
Domain Expertise
Our extensive experience in AI and agriculture projects allows us to deliver exceptional data annotation services tailored specifically to the needs and requirements of the agricultural industry.
Flexible Business Model
With our flexible business models, we excel in short-term POC or R&D agricultural initiatives. Clients often require precise computer vision algorithms to address specific needs, and we efficiently annotate limited datasets within tight timelines.
Adjustable Timeframes
Our agile timeline adaptation ensures a quick project launch (typically 1-3 weeks from initial interaction) and efficient completion within desired timelines. Leveraging expertise and a robust annotation environment, we prioritize timely delivery to meet client requirements.
Why Choose Agriculture Data Annotation Services at Label Your Data?
Our company holds certifications for PCI DSS (level 1) and ISO:27001, and we adhere to the regulations outlined by GDPR, CCPA, and HIPAA. With 10+ years of experience and 500+ specialists on board, we provide customized data annotation services in agriculture for enterprise and R&D projects in 55 languages.
Our Success Stories
Main challenge:
Adapting the labeling process to the client’s platform
Solution:
A flexible team performing image annotation, labeling of satellite imagery, and geotagging using the client’s tooling.
Data Annotation for an Orchard Analytics Platform
Our UK-based client, a software company specializing in orchard analytics, asked us to label 5,000 apple tree images. Our annotators had to identify well-shown fruits, occluded ones, and classify ripeness levels. Additionally, we provided labeling for satellite imagery and performed geotagging. Using the client’s platform, we ensured seamless utilization of valuable insights produced through labeling. This comprehensive dataset fueled the development of an analytics platform, empowering farmers to enhance harvest care.
Main challenge:
Understanding the anatomical features of horses for quality labeling
Solution:
A specialized training for the team in skeleton key point annotation.
Key Point Annotation for a Data Science Consulting Firm
We collaborated with a leading Data Science Consulting company based in the EU, specializing in AI-powered solutions for diverse industries. The task involved annotating 30,000 horse images with skeleton key points. The client had direct access to the platform to be able to review our progress, provide feedback, and suggest corrections for precise annotations. Leveraging our proprietary annotation tooling, we delivered this tailored data annotation in agriculture service.
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FAQs
What is the role of AI in agriculture?
The transformative power of AI in agriculture encompasses precision farming, optimized crop management, and data-driven decision-making, revolutionizing the industry. Yet, no AI project can be feasible without high-quality data annotation in the agriculture industry.
What data is important to farmers?
Accurate and timely data is crucial for farmers to optimize agricultural productivity by informing decisions on weather, soil moisture, crop health, and market trends. Professional data annotation services in farming can greatly leverage this data for AI systems.
How are data processing and annotation used in farming?
Data processing and data annotation in agriculture are essential, as they convert raw agricultural data into structured datasets for valuable insights, AI model training, and optimized farming practices like crop management, resource allocation, and pest control.