This dataset is useful for training and testing object detection models, especially those focused on understanding urban scenes and safety applications.

Containing labelled fruit images to train object detection systems.

YOLOv8 Car Object Detection Dataset

Introducing the SkyFusion dataset, designed for detecting tiny objects in satellite images. While many datasets focus on larger structures

As biometric security becomes more common, we can’t ignore the risk of silicone masks in biometric attacks. Our AI data collection company is dedicated to giving you all the latest info on this changing threat.

Adheres to ethical data usage standards, ensuring all content is appropriately licensed and suitable for a broad range of users.

A “roads segmentation dataset” typically consists of images or aerial photographs that have been annotated to highlight and classify road areas within the images. This dataset is commonly used in computer vision and machine learning tasks, particularly for training and evaluating algorithms related to road detection and segmentation. The annotations in such a dataset provide pixel-level or object-level labels to distinguish road areas from other elements in the images, making it valuable for applications like autonomous driving, urban planning, and map generation. Researchers and developers use roads segmentation datasets to train models to identify and segment roads accurately from various types of imagery.

At Globose Technology Solutions, we’re using the COIL-100 Dataset to improve object recognition solutions. Our advanced algorithms are making a difference in areas like industrial automation and security systems.