Computer Vision

Data: Your Key to Successful Autonomous Mobility

Appen is the leader in Data for the AI Lifecycle. This webinar explores use cases and challenges that our mobility clients see from data sourcing, data preparation, and model evaluation. Follow along as our experts discuss and demo the technologies and processes that were used to enable success for both in-cabin experiences and out-of-car data with ADAS systems and autonomous vehicles. Wilson …

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 …

Data-Centric Computer Vision

Approaches, Applications, and Best Practices using the Appen Data Annotation Platform Human vision systems have the advantage of learning from a lifetime of experiences how to contextualize the things we see. Machine learning models, on the other hand, usually need a substantial number of real-world scenarios to learn from to be able to product reliable computer vision (CV) outputs. These …

Machine Vision vs. Computer Vision — What’s the Difference?

Artificial Intelligence is an umbrella term that covers several specific technologies. In this post, we will explore machine vision (MV) vs. computer vision (CV). They both involve the ingestion and interpretation of visual inputs, so it’s important to understand the strengths, limitations, and best use case scenarios of these overlapping technologies. The Beginning of Computer Vision Researchers began developing computer-enabled …

What is Computer Vision?

Everything You Need to Know About Computer Vision With its recent surge in popularity, computer vision (CV) has become one of the fastest-growing fields of artificial intelligence (AI). The intended purpose of computer vision technology is to mimic the complexity of the human vision system, which includes eyes, receptors, and the visual cortex. This intricate system, when duplicated, gives machines …

CVPR 2019: Progress and Challenges in the Field of Computer Vision

The annual Computer Vision & Pattern Recognition conference is packed with insightful presentations and top industry experts. With nearly 10,000 attendees and 1,200 papers, CVPR 2019 in Long Beach, CA was no exception. In this post, we’ll take a brief look at some notable presentations delivered at the conference for solving numerous computer vision and pattern recognition challenges. Data augmentation …

Three of the Most Innovative Automotive AI Applications at AutoSens Detroit

Appen recently exhibited at AutoSens Detroit, where we shared our approach to data collection and annotation for in-car navigation, infotainment, and monitoring, as well as autonomous vehicle solutions. Here are some of the coolest innovations in automotive AI, as spotted by our team: Mercedes Benz’s Intelligent Interior Volker Entenmann, Senior Manager of UI Functions at Daimler AG, shared how Mercedes-Benz …

How to Create Training Data for Computer Vision Use Cases

For simple computer vision projects, such as recognizing a pattern in a group of images, publicly available image datasets will usually suffice to train your machine learning models. But for more complex CV applications, how can you get the vast amounts of training data you need to create an accurate solution? In this post, we explain training data requirements for …

Computer Vision vs. Machine Vision — What’s the Difference?

Artificial Intelligence is an umbrella term that covers several specific technologies. In this post, we will explore machine vision (MV) and computer vision (CV). They both involve the ingestion and interpretation of visual inputs, so it’s important to understand the strengths, limitations, and best use case scenarios of these overlapping technologies. Researchers began developing computer-enabled vision technologies as early as …

Want to Build a Better Computer Vision System? Give it the Right Training Data.

For a company to build a comprehensive dataset of annotated images takes considerable time and resources. Outsourcing the data collection and annotation efforts can help companies scale quickly.

Benefits of Artificial Intelligence Enhancing the Business Landscape

The Benefits of Artificial Intelligence are Enhancing the Business Landscape

The unstoppable march of Artificial Intelligence (AI) and machine learning is already touching our lives in so many ways. But its effects have only just begun to take hold.