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1,437 Remote Sensing Images - Object Segmentation and Detection Data in Airport and Port Scenes
Remote sensing
Airport
Port
Object detection
Object segmentation
1,437 Remote Sensing Images - Object Segmentation and Detection Data in Airport and Port Scenes. The scenes cover different countries, various airports and ports, and can be used for tasks such as object detection and semantic segmentation.
This is a paid datasets for commercial use, research purpose and more. Licensed ready made datasets help jump-start AI projects.
labels, bounding boxes and sematic segmentations of objects
Data format
the format of remote sensing image and segmentation demo is .tif, the format of segmentation mask is .png, the format of annotation file of segmentation and bounding box is .json
Annotation accuracy
above 95%, including object bounding box, sematic segmentation and labes
What types of computer vision applications can Nexdata’s datasets support?
Nexdata’s computer vision datasets support a wide range of AI applications, including image classification, object detection, image segmentation, facial and human-related recognition, scene understanding, autonomous driving, and other visual perception tasks. Depending on the dataset, data may include images, videos, bounding boxes, polygons, keypoints, segmentation masks, text annotations, and other structured labels.
Can Nexdata customize Computer Vision datasets based on our specific requirements?
Yes. If our off-the-shelf Computer Vision datasets do not fully meet your requirements, Nexdata provides flexible custom data collection, annotation, and curation services. We can customize data based on your target objects, environments, scenarios, camera specifications, geographic locations, data volume, annotation formats, and quality standards to support specific model training and evaluation needs.
How does Nexdata ensure the quality and scalability of its Computer Vision datasets?
Nexdata applies multi-stage quality control throughout data collection, annotation, validation, and delivery. Depending on project requirements, we can implement customized annotation guidelines, multi-level reviews, consistency checks, and quality sampling to ensure dataset accuracy and consistency. Our data collection and processing capabilities can also be scaled to support large-volume Computer Vision projects.
Specifications
Sample
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