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How to streamline your Instance Segmentation labeling experience with

How to streamline your Instance Segmentation labeling experience with

Instance Segmentation is a prevalent Computer Vision task, as it might help ease your pain across various industries and tasks. In short, Instance Segmentation techniques help Data Scientists find distinct instances on an image, classify, and segment them, producing class labels and pixel-perfect segmentation masks.

In general, one may say that Instance Segmentation can come in handy for anyone as it is widely used by businesses, governments, and other actors. Instance Segmentation real-life application fields include:

However, nowadays, data annotation might be a bottleneck for AI startups as the conventional labeling approach is both costly and time-consuming. Hasty’s data-centric ML platform addresses the pain and automates 90% of the work needed to build and optimize your dataset for the most​ advanced use cases ​ with our self-learning assistants using AI to train AI.

Below is a video tutorial showing how to streamline your Instance Segmentation experience with Hasty. Want to make your annotation workflow easier? Watch the video and see how we can help.

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