AI agriculture enables disease detection, quality grading, and environmental forecasting to boost productivity and resilience.
Use image recognition to detect crop diseases and pests, and provide treatment recommendations to reduce yield loss.
Analyze images and sensor data to assess ripeness and defects, enabling automated grading and improving market competitiveness.
Combine satellite, weather, and sensor data with AI models to predict crop growth, drought, and flood conditions.
This dataset is for horse individual identification, providing high-quality images and annotation information.
This dataset provides operational behavior data of agricultural experiment personnel, suitable for object detection tasks.
This dataset provides high-quality aerial images of terraced terrain, supporting object detection tasks.
This dataset is a high-quality land use cover remote sensing dataset focused on the agricultural field, supporting object detection tasks.
This dataset focuses on the classification of remote sensing images of farmland types, aiding in agricultural monitoring and research.
This dataset provides high-quality winnowing scene images for the agricultural sector, aiding crop identification and monitoring.
This dataset is used for classification of tea leaf drying processes, aiding the intelligent and standardized agricultural production.
This dataset focuses on keypoint detection of farmer planting poses, supporting the development of precision agriculture.
This dataset aims to enhance the monitoring efficiency of sprayer usage, aiding agricultural automation.
This dataset is used to study spray nozzle trajectories, providing data support for precision agriculture.
The pesticide spraying scene classification dataset is used to enhance the intelligence level of agricultural spraying operations.
This dataset provides high-quality target detection image data for pesticide spraying to assist in the enhancement of agricultural safety monitoring technology.
This dataset is used to recognize agricultural spraying actions, aiding the development of smart agriculture.
This dataset provides high-quality image data for the task of spray droplet coverage segmentation, supporting the development of precision agriculture.
This dataset focuses on the target detection of farmland pesticide spraying operations, aiming to enhance agricultural work efficiency.
This dataset provides high-quality image data for studying the effectiveness of agricultural machinery in weed control, supporting tasks such as object detection and image recognition.
This dataset provides high-quality image data for agricultural object detection, supporting the intelligent upgrade of agricultural machinery weeding operations.
This dataset focuses on the safety inspection of weeding operations, providing high-quality image support for intelligent agricultural monitoring.
This dataset is used for identifying weed coverage in farmland, aiding the development of smart agriculture.
This dataset focuses on the classification of weed species, aiding the development of precision agriculture.
Lightning-Fast Response, 1:1 Technical Validation