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Case Study
Enhancing Strawberry Growth Monitoring with Accurate Data Annotation
Strawberry Growth Image Annotation Project
Platform
53 Refugees
in Syria impacted through this project
374,334 images
annotated with ultra high precision
Annotation Type
Bounding Box + Polygon
Classification
Growth Analysis
Challenge :
Our client faced difficulties in accurately detecting and identifying the true features of strawberry plants due to partial obstruction by leaves and other obstacles.
This issue made it hard to differentiate between the various growth stages of the strawberries, leading to challenges in determining which fruits were ready for harvest, sorting, and storage.
Solution
Our mission was to provide precise and effective data annotation services to enhance the client’s ability to identify the exact shape and growth stages of the strawberries.
By leveraging our expertise in image annotation, we aimed to classify the fruits based on agreed-upon criteria, making it easier for the client to manage the harvesting and sorting process efficiently.
FEATURES
Implementation:
Expert Annotation Team
We assembled a specialized team with extensive experience in agricultural crop and fruit image annotation. This team used advanced tools and techniques to accurately mark and classify the strawberries in the images.
Utilization of Cutting-Edge Tools
We utilized the CVAT platform to create both bounding box and polygon annotations, ensuring precise identification of each strawberry and its growth stage.
Multi-Stage Classification
By categorizing the strawberries according to their different maturity stages, we helped the client precisely identify ripe fruits, facilitating better decision-making for harvesting and sorting.
Result:
Through the accurate annotation of strawberry images, we helped the client achieve the following outcomes:
- Improved Growth Stage Detection: Our annotations enabled the client to clearly recognize the different growth stages of strawberries, making it easier to manage the harvest and storage process.
- Enhanced Efficiency in Harvesting: By providing detailed and precise datasets, the client was able to optimize the identification of ripe strawberries, resulting in more effective and timely harvesting and sorting operations.
- Streamlined Workflow: The high-quality, annotated datasets ensured smooth operations, allowing the client to rely on consistent and accurate data to improve their productivity.
Conclusion
Subul’s expertise in agricultural image annotation significantly contributed to the client’s ability to monitor the growth of their strawberry crops with high accuracy. By delivering well-annotated datasets, we empowered the client to improve their harvesting and sorting processes, ultimately boosting productivity and ensuring more efficient management of their strawberry farms.
How Subul Data Annotation Works For You
Personalized and Fully Managed
Get a dedicated project manager to handle everything from guidelines to quality control, ensuring a seamless experience from start to finish.
Multilayer Quality Control
Experience the assurance of multi-tiered QC processes, including peer review and expert checks, guaranteeing a minimum accuracy of 98%.
Diverse and Scalable Workforce
Access a diverse team of industry experts, assembled within 72 hours, tailored to fit your project's specific needs and scale.
Unbiased and Compliant
Rely on our rigorously trained workforce for unbiased data, perfectly aligned with international privacy and AI standards.
Express Delivery
Benefit from our dynamic workforce, capable of rapidly scaling up to meet tight deadlines and ensure swift project delivery.
Direct Social Impact
Make a difference with every project; our entire workforce comes from refugee and disadvantaged backgrounds, contributing to social goals.
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