Understanding Computer Vision & Image Annotation
Any computing system fundamentally works on the basic concepts of input and output. Whether it is a rudimentary calculator, our all-requirements-met smartphone, a NASA supercomputer predicting the effects of events occurring thousands of light-years away, or a robot-like J.A.R.V.I.S. helping us defend the planet, it’s always a response to a stimulus — much like how we humans operate — and the algorithms which we create teach the process for the same. The specifications of the processing tools determine how accurate, quick, and advanced the output information can be.
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Image annotators are playing a key role in machine learning (ML) and AI development. Actually, in machine learning, certain data sets are used to train the algorithm, that learns the patterns and make the productions in real-life use as per the data used.
After texts, images are the major source used as a training data for machine learning. And to make such images recognizable to machines, annotation is done for computer vision. And experts who annotate such images, are known as image annotators.
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