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 provides accurate operation image data for weed removers, supporting object detection tasks to promote agricultural intelligence.
This dataset aims to enhance weed removal efficiency through object detection technology, providing data support for smart agriculture.
This dataset is for target detection of irrigation machinery to aid the development of smart agriculture.
This dataset provides high-quality image data for monitoring the utilization of agricultural water resources, supporting object detection tasks.
This dataset provides high-quality images and annotations for farmland irrigation mist segmentation, supporting the development of precision agriculture.
The farmland irrigation equipment detection dataset provides high-quality target detection data for intelligent agricultural monitoring.
This dataset is used to support the classification of irrigation scenarios in the agricultural field, aiding the development of intelligent agriculture.
This dataset is dedicated to providing high-quality image data support for sweet potato size estimation and object detection.
The Sweet Potato Automatic Counting Dataset provides high-quality object detection data for smart agriculture, aiding in agricultural automation.
The Sweet Potato Quality Detection Dataset is a high-quality image dataset for object detection, aimed at improving the efficiency of sweet potato quality assessment.
Sweet potato instance segmentation dataset to aid agricultural intelligence and pest detection.
This dataset is intended to improve the accuracy and efficiency of sweet potato target detection, promoting the development of smart agriculture.
The Raspberry Fruit Detection Dataset is designed for intelligent monitoring in agriculture.
Raspberry variety classification dataset to support intelligent agriculture in raspberry variety recognition and classification research.
This dataset focuses on the detection of manual harvesting actions to aid the development of smart agriculture.
This dataset provides high-quality image data for grassland moisture and health monitoring, aiding intelligent agriculture management.
This dataset provides high-quality image data for remote sensing classification of grassland types.
This dataset provides high-quality images for grass maturity detection to support object detection tasks in the agricultural field.
The Field Grass Navigation Dataset is designed for agricultural object detection tasks, providing high-quality annotated image data.
This dataset provides high-quality images for monitoring and analyzing the stages of grass growth.
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