The Future of Computer Vision is Data-Centric

Cullen Billhartz, Machine Learning and Computer Vision Technologist at The Boeing Company and Kuo-Chin Lien, Data Scientist and Head of Computer Vision at Appen

Watch On-Demand to learn more about data and annotation best practices for any organization looking to leverage AI, specifically computer vision, within their company. Learn from our practical examples and tool showcases, and get answers for your questions from our expert guests.

Instead of needing a lifetime of input to be able to react in the real world, great computer vision solutions leverage the right combination of models and datasets that match the task at hand. Today, you need to have the right data-centric approach to build successful computer vision applications, using advanced tools and specialized annotators.

You might be dealing with diverse data types, such as:
• 2D images and video (taken from an SLR or infrared camera)
• 3-D images and video (taken from a camera or scanner)
• Sensor data (taken from RADAR or LiDAR technology).
• A mix of the above

By using the Appen Data Annotation Platform, anyone looking to improve their computer vision models can output the highest and most accurate training data to achieve the best performance in production.