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 focuses on seedling recognition, aiming to enhance the automation and accuracy of agricultural monitoring.
This dataset is used to identify the health status of poultry, aiding agricultural health monitoring and disease warning.
This dataset focuses on the automated detection and statistics of poultry quantity, supporting agricultural monitoring.
This dataset focuses on the classification of goose and duck breeds, aiding agricultural management and species identification.
This dataset focuses on the semantic segmentation of farm people and vehicles, promoting intelligent agricultural management.
This dataset provides rich data on agricultural product transportation scenes, aiming to enhance the efficiency of agricultural logistics.
This dataset provides high-quality images of farm transportation tools to improve the accuracy of agricultural machinery recognition.
The Farmland Plot Segmentation Dataset provides high-quality image segmentation data for precise agricultural management.
The Onion Classification and Segmentation Dataset is an image dataset focused on the agricultural field, aiming to enhance the intelligence level of crop classification and pest and disease detection.
The Onion Harvest Detection Dataset provides precise target detection data for agricultural intelligence, aiding in enhancing harvest efficiency.
This dataset focuses on the monitoring and analysis of cattle grazing and grassland coverage, aiding the development of precision agriculture.
The cattle behavior recognition dataset provides high-quality target detection data for intelligent agricultural monitoring, supporting the development of behavior recognition technology.
The Cattle Body Contour Segmentation Dataset provides high-quality semantic segmentation image data for agricultural monitoring, aiding precision agriculture.
The cattle detection dataset provides high-quality target detection support for agricultural monitoring.
This dataset provides high-quality images of tomatoes and their quality grading to support agricultural intelligence.
The Tomato Picking Navigation Dataset is a high-quality image dataset designed for agricultural automation target detection.
This dataset provides high-quality images for greenhouse tomato environment monitoring, supporting object detection tasks.
This dataset provides high-quality monitoring data of tomato growth stages for the agricultural sector, aiding the development of smart agriculture.
This dataset focuses on tomato fruit counting to aid the development of smart agriculture.
The Tomato Peduncle Keypoint Dataset is a high-quality target detection dataset designed for intelligent agricultural monitoring.
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