CloudFactory Earns HIPAA Compliant Business Associate Validation

CloudFactory Earns HIPAA Compliant Business Associate Validation

CloudFactory is a HIPAA-compliant business associate, committed to safeguarding personal health information for Medical AI and healthcare data projects.

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Levels of Driving Automation: When is AI Applied? [Infographic]

Levels of Driving Automation: When is AI Applied? [Infographic]

Learn how the levels of driving automation in autonomous vehicles are determined by the presence of ADS with AI technology or ADAS.

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Drone Delivery and AI: GPS-Free Navigation

Drone Delivery and AI: GPS-Free Navigation

GPS free navigation technology enables the safety, scalability, and productivity of drone deliveries in urban areas where satellite signals can be lost.

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ICYMI: Key Insights into the Future of Drone Inspections

ICYMI: Key Insights into the Future of Drone Inspections

A panel of drone tech pioneers talks about how AI and computer vision, backed by high-quality data, is shaping the future of drone inspections.

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4 Reasons Doctors Shouldn’t Annotate Data for Medical AI

4 Reasons Doctors Shouldn’t Annotate Data for Medical AI

Here are four reasons that doctors shouldn't waste time on tedious data labeling and a solution to accelerate medical AI data training data pipelines.

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Understanding LiDAR Data in Autonomous Driving

Understanding LiDAR Data in Autonomous Driving

LiDAR data labeling needs to be precise in autonomous driving as the data gives vehicles a 3-D image to interpret surroundings safely.

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Drone Delivery and AI: Object Detection and Collision Avoidance

Drone Delivery and AI: Object Detection and Collision Avoidance

This blog post is about how AI-enabled drones use object detection and collision avoidance computer vision technology for drone delivery at scale.

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Where Do ADS and ADAS Fall Into The Levels of Driving Automation?

Where Do ADS and ADAS Fall Into The Levels of Driving Automation?

This article discusses how the levels of driving automation are determined by the presence of ADS with AI technology or ADAS.

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Complex Geospatial Data Labeling: Trends, Challenges, Solutions

Complex Geospatial Data Labeling: Trends, Challenges, Solutions

Geospatial data is fueling innovation in many sectors. Read on if your business needs to scale its data labeling operations while maintaining quality.

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Medical AI Security and Data Privacy in the Age of Computer Vision

Medical AI Security and Data Privacy in the Age of Computer Vision

Are you considering outsourcing data labeling work while developing medical AI or computer vision solutions? Read these data security tips.

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Doctors Shouldn't Annotate Medical Data. Expert Annotators Should.

Doctors Shouldn't Annotate Medical Data. Expert Annotators Should.

Doctor shortages are impacting healthcare innovators’ ability to label data for computer vision solutions. Outsourcing the work will help.

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5 Key Questions to Ask Before Outsourcing Healthcare Data Labeling

5 Key Questions to Ask Before Outsourcing Healthcare Data Labeling

Computer vision improves patient care, streamlines medical decisions, and lowers costs. Ask these questions before outsourcing healthcare data annotation.

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4 Use Cases on Why Using Drones to Collect Data Improves Inspections

4 Use Cases on Why Using Drones to Collect Data Improves Inspections

These four use cases examine why using drones to collect data makes drone inspections safer, more accurate, and more efficient than manual inspections.

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Breaking Down The Levels of Drone Autonomy

Breaking Down The Levels of Drone Autonomy

The demand for drone autonomy is rapidly increasing. See how CloudFactory defines the levels of drone autonomy.

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The 4 Biggest Hurdles for Real-Time Geospatial Data Labeling

The 4 Biggest Hurdles for Real-Time Geospatial Data Labeling

The real-time use cases for geospatial data are practically limitless, but data-labeling on such an enormous scale remains a major challenge.

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Does Not Compute: The NLP Context Conundrum

Does Not Compute: The NLP Context Conundrum

The nuances of language can be difficult for a machine to understand, hence the need for human input to accelerate testing and ensure quality control.

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