Deepen AI

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Our annotation tools and services can be customized to meet all annotation needs

Our annotation tools and services can be customized to meet all annotation needs

Deepen’s AI new joint labeling feature combines labeling of 3D semantic segmentation with 3D and 2D bounding boxes

We are able to combine annotation of 3D semantic segmentation with 3D and 2D bounding boxes. Thereby provide the best ROI to enterprises – while maintaining the highest quality.”

— Mohammad Musa, CEO and Co-Founder at Deepen AI

SANTA CLARA, CALIFORNIA, UNITED STATES, January 4, 2023 /EINPresswire.com/ — Deepen AI, a world leader in multi-sensor tools and annotation services, today announced an exciting new feature that combines 3D instance segmentation with 3D and 2D bounding boxes – all in one go. This feature brings down the effort needed for annotation by a third and provides the best ROI across the industry.

The use cases for 3D segmentation have been on a steady rise because of their wide applications. 3D semantic and instance segmentation allows enterprises to determine the class, shape, size, and other properties of the objects down the point level. However, 3D segmentation is a challenging and expensive task. Teams were blocked from accessing this level of ground truth training and validation data due to cost.

Combining data operation efficiencies with an experienced labeling team and AI-powered annotation tool, we are able to provide our customers with the highest ROI and quickest turnaround – all while maintaining high-quality output.

Deepen AI also provides enterprises with features to easily manage, track and increase productivity:
– Expert in-house team – Specialized in-house managed and trained workforce.
– Advanced reporting – To support all business needs to give clients key information with a click of a button.
– Automation – Deepen AI’s smart labeling function that pre-labels the data to increase efficiency & reduce man-hours by more than 85%.
– Quality Assurance – Built-in QA flow allows enterprises to easily verify the quality of processed data to maintain quality standards.

“The demand for high-quality 3D semantic segmentation data is increasing rapidly. With our AI-powered annotation tool, we are able to combine annotation of 3D semantic segmentation with 3D and 2D bounding boxes. Thereby provide the best ROI to enterprises – while maintaining the highest quality.” – Mohammad Musa, CEO, and Founder, Deepen AI

By leveraging years of experience, Deepen AI has been able to regularly push the boundaries to innovate and bring the best-in-class features to their customers. Deepen AI’s annotation tool is industry agnostic and can be used across all key industries such as Automotive, Robotics, Agriculture, Drones, etc.

Deepen AI’s annotation tools support all types of key cases like:
– Bounding boxes
– Semantic segmentation
– Polylines
– Scenario labeling
– Keypoints

Deepen AI’s annotation tool is capable of handling large point-cloud sequences with up to 200 million points on an average laptop with their proprietary advanced point-cloud rendering optimization technology. Deepen AI is able to annotate large volumes of point clouds with speed and accuracy.

Deepen AI’s suite of products also includes Deepen Calibrate – Deepen Calibrate can cut the time spent on calibrating multi-sensor data from hours to minutes, enabling accurate localization, mapping, sensor fusion perception, and control.

To learn more about Deepen AI’s products and services, you can visit www.deepen.ai or write to them at info@deepen.ai.

About Deepen AI

Deepen AI is a Silicon Valley-based startup and the only safety-first data lifecycle tools and services company focused on machine learning and AI for autonomous systems. With tools and services that are customizable to suit the needs of enterprises as well as start-ups they have happy customers of every size across the globe. Visit Deepen.ai for more information.

Contacts
Mohammad Musa, Co-Founder & CEO
info@deepen.ai
+1 (650) 560 -7130

Mohammad Musa
Deepen AI
+1 650-560-7130
email us here
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