Showing posts with the label computer vision

Making Visual Data a First-Class Citizen

“ Above all, don't lie to yourself. The man who lies to himself and listens to his own lie come…

Three Fundamental Dimensions for Thinking About Machine Learning Systems

Today, let's set cutting-edge machine learning and computer vision techniques aside. You probab…

Mobileye's quest to put Deep Learning inside every new car

In Amnon Shashua's vision of the future, every car can see .  He's convinced that the key t…

Deep Learning vs Machine Learning vs Pattern Recognition

Lets take a close look at three related terms (Deep Learning vs Machine Learning vs Pattern Recogni…

10% of our Kickstarter campaign total will go to free High School Student technology licenses

Dear Kickstarters, technology enthusiasts, and STEM educators, We’re happy to announce a new reward…

Tracking points in a live camera feed: A behind-the-scenes look at the VMX Project webapp

In our computer vision startup, vision.ai , we're using open-source tools to create a one-of-a-…

Understanding the Visual World, one 3D reconstruction at a time

The first generation of datasets in the computer vision community were just plain old images --  si…

VMX: Teach your computer to see without leaving the browser, my Kickstarter project

I’ve spent the last 12 years of my life learning how machines think, and now is time to give a litt…

Brand Spankin' New Vision Papers from ICCV 2013

The International Conference of Computer Vision, ICCV, gathers the world's best researchers in …

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