This dataset focuses on the semantic segmentation of seedlings and soil, aiding the development of precision agriculture.

This dataset is used for carrot quality grading, supporting target detection tasks.

The Musella Lasiocarpa Image Recognition Dataset for Garden Flowers is a high-quality image dataset used to identify specific varieties of flowers.

The Orchard Scene Recognition Dataset provides high-quality images and annotations for agricultural object detection, aiding in orchard management and monitoring.

This dataset combines visual data from vineyards with field environment data to build a yield prediction dataset for AI model training.

The Magnolia Recognition Image Dataset focuses on the precise identification and classification of magnolia species.

The Garden Flower Paphiopedilum Recognition Image Dataset effectively supports flower recognition and analysis in the agriculture and forestry industries.

This dataset provides high-quality target detection images for crop growth stage monitoring.

This dataset is used for the recognition of asparagus packaging labels, supporting supply chain traceability and anti-counterfeiting applications.

This dataset provides high-quality image data support for hand detection in tea leaves picking, aiding the development of smart agriculture.

This dataset is used to analyze the correlation between the color characteristics and maturity of strawberries to enhance agricultural intelligence.

This dataset is for target detection of irrigation machinery to aid the development of smart agriculture.

The Field Seedling Localization Dataset focuses on providing high-quality target detection data for precision agriculture.

The Garden Flower Eyelash Rhododendron Recognition Image Dataset focuses on accurate identification and classification of eyelash rhododendron varieties.

This dataset focuses on the recognition of cucumber picking scenes in the field, aiming to improve the level of agricultural intelligence.

This is an object detection dataset for corn leaf disease recognition.

The Cattle Body Contour Segmentation Dataset provides high-quality semantic segmentation image data for agricultural monitoring, aiding precision agriculture.

The weed detection dataset provides high-quality object detection data for the agriculture field, aiding crop health management.

This dataset is used to detect the growth status of crops under waterlogged conditions, aiding intelligent agricultural management.

The drought disaster detection dataset is used for AI-supported agricultural monitoring and disaster assessment.