The Farmland Fence Detection Dataset provides rich image data for agricultural object detection, aiding intelligent farmland management.

A comprehensive dataset of occluded images of instant noodle products for advanced image recognition tasks.

This dataset provides images for wheel hub defect detection to enhance automotive quality control.

A comprehensive dataset for detecting and monitoring high pressure oil pumps in industrial settings.

This dataset is dedicated to providing high-quality image data for farmland and woodland boundary detection.

This dataset focuses on the classification and object detection of rural labor living scenes to support the development of agricultural intelligence.

This dataset is used for the automatic recognition and monitoring of highway traffic congestion.

The Bald Face Recognition Image Dataset focuses on improving the accuracy and security applications of bald face recognition.

Identify leaf rot disease in durian plantations through a high-quality image dataset.

A dataset focused on detecting failures in electric rice cooker switch buttons.

High-quality image data for detecting yellow peach weevil pests in durian planting.

This dataset provides rich data on agricultural product transportation scenes, aiming to enhance the efficiency of agricultural logistics.

The Skirt AI Outfit Image Dataset provides high-quality outfit images for e-commerce, enhancing the user shopping experience.

This dataset focuses on the detection and verification of three-way catalytic converters in industrial settings.

The garage vehicle type image recognition dataset is used to improve the accuracy of vehicle detection and classification.

This dataset is used to recognize the occupation status of corridors and public passages.

This dataset focuses on motorcycle traffic accident risk analysis, providing high-quality image data and detailed annotations.

This dataset aims to provide high-quality T-shirt try-on composite images to enhance the online shopping experience.

This dataset is used for farmland pest species recognition, containing a wealth of image samples and annotation information.

Pair UAV aerial imagery with segmentation labels to identify and map rapeseed field parcels.