Computational Needs for Computer Vision (CV) in AI and ML Systems. In this article, take a look at computational needs for computer vision in AI and ML systems.
Computer vision (CV) is a major task for modern Artificial Intelligence (AI) and Machine Learning (ML) systems. It’s accelerating nearly every domain in the tech industry enabling organizations to revolutionize the way machines and business systems work.
Academically, it is a well-established area of computer science and many decades worth of research work have gone into this field. However, the use of deep neural networks has recently revolutionized the CV field and given it new oxygen.
There is a diverse array of application areas for computer vision. In this article, we briefly show you the common challenges associated with a CV system when it employs modern ML algorithms. For our discussion, we focus on two of the most prominent (and technically challenging) use cases of computer vision:
Both of these use cases present a high degree of complexity, along with other associated challenges.
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Computer Vision (CV) is nowadays one of the main application of Artificial Intelligence (eg. Image Recognition, Object Tracking, Multilabel Classification). In this article, I will walk you through some of the main steps which compose a Computer Vision System.
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