Image Annotations
Annotate at scale
The days of a single labeler laboriously (and slowly) identifying all elements and objects within an image…are over! Our patent-pending, multiple-image processing technology breaks down a single image into tens/hundreds of data layers and from that creates micro-tasks, prompting millions of Tasqers to label individual parts of an image simultaneously. Their job duties include (but are not limited to) training the model under constant supervision, including model details like prediction and function loss.
Continuous optimization
When model predictions are positively validated by a human, results are fed back into the model. With an ever growing amount of data in the world, the need for scalability, and speed is crucial. We accelerate our customers’ needs and find new paths and solutions to improve our customers’ and users’ experience.
Our Machine Learning models are improved through a constant and dedicated approach of our Tasqers, which are devoted to improving the Machine Learning data models worldwide. We as a company encourage a multi-cultural, diverse, multilingual approach so our customers get a highly valuable, unbiased content-based annotations.
We use advanced Machine Learning capabilities to optimize and accelerate the entire process of labeling, tagging, validation, annotation and more. Every object is reviewed separately by multiple Tasqers for deeper understanding and validated until the correct labeling quality is achieved.
The result: Fast, scalable, accurate datasets.