17
OctUsing Annotation to Detect Fraud on E-commerce Platforms
E-commerce fraud evolves daily—from fake listings to account takeovers. This guide shows how annotation transforms raw platform data into training signals for robust, real-time fraud detection systems, with practical schemas, workflows, and quality controls you can apply now.
06
OctTracking Climate Impact on Fields Through Time-Series Imagery Annotation
Explore how time-series imagery annotation helps identify and predict climate effects on agricultural fields. Learn how Learning Spiral AI enables smarter, AI-driven environmental insights with high-quality data labeling for precision farming and climate research.
30
SepDifferentiating Crops from Weeds: Annotation Best Practices
In modern farming, crop and weed differentiation with AI has become essential. Accurate data annotation empowers AI systems to[…]
25
SepUsing Manual Annotation for Livestock Monitoring: A Foundational Step Toward Smarter Farming
In the era of smart agriculture, data-driven technologies are reshaping traditional farming practices. One of the most critical elements[…]
25
SepAnnotating Agricultural Diseases: Early Detection with AI
In the age of precision agriculture, early detection of crop diseases is becoming vital for food security, yield protection,[…]
25
SepThe Role of Annotated Drone Images in Crop Monitoring
Introduction In today’s data-driven agriculture, annotated drone images in crop monitoring are revolutionizing how farmers manage their fields. Drones[…]
