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Deep learning advances are boosting computer vision -- but there's still clear limits

#artificialintelligence

This article is part of Demystifying AI, a series of posts that (try to) disambiguate the jargon and myths surrounding AI. Since the early days of artificial intelligence, computer scientists have been dreaming of creating machines that can see and understand the world as we do. The efforts have led to the emergence of computer vision, a vast subfield of AI and computer science that deals with processing the content of visual data. In recent years, computer vision has taken great leaps thanks to advances in deep learning and artificial neural networks. Deep learning is a branch of AI that is especially good at processing unstructured data such as images and videos.


Deep learning advances are boosting computer vision -- but there's still clear limits

#artificialintelligence

This article is part of Demystifying AI, a series of posts that (try to) disambiguate the jargon and myths surrounding AI. Since the early days of artificial intelligence, computer scientists have been dreaming of creating machines that can see and understand the world as we do. The efforts have led to the emergence of computer vision, a vast subfield of AI and computer science that deals with processing the content of visual data. In recent years, computer vision has taken great leaps thanks to advances in deep learning and artificial neural networks. Deep learning is a branch of AI that is especially good at processing unstructured data such as images and videos.


Computer vision applications: The power and limits of deep learning

#artificialintelligence

This article is part of Demystifying AI, a series of posts that (try to) disambiguate the jargon and myths surrounding AI. Since the early days of artificial intelligence, computer scientists have been dreaming of creating machines that can see and understand the world as we do. The efforts have led to the emergence of computer vision, a vast subfield of AI and computer science that deals with processing the content of visual data. In recent years, computer vision has taken great leaps thanks to advances of deep learning and artificial neural networks. Deep learning is a branch of AI that is especially good at processing unstructured data such as images and videos.


What is the Working of Image Recognition and How it is Used?

#artificialintelligence

Before a classification algorithm can do its magic, we need to train it by showing thousands of cat and non-cat images. The general principle in machine learning algorithms is to treat feature vectors as points in higher dimensional space. Then it tries to find planes or surfaces (contours) that separate higher dimensional space in a way that all examples from a particular class are on one side of the plane or surface. To build a predictive model we need neural networks. The neural network is a system of hardware and software similar to our brain to estimate functions that depend on the huge amount of unknown inputs.


Computer Vision Applications in 10 Industries

#artificialintelligence

Computer vision, or abbreviated to CV, is an increasingly important technology in the field of artificial intelligence. Those involved in its development believe that it has endless possibilities and a wealth of applications in a range of fields. These include developing non-invasive health care treatments to self-driving vehicles and virtual shopping experiences. Through the course of this article, we will seek to explain exactly what computer vision is and the applications of computer vision in all major industries. We will also look at its current limitations as well as how it is already being applied. Computer vision has the potential to transform a number of operations and sectors. As it grows in importance, its potential and applications will be key to helping it enhance your organization. Computer vision is a branch of artificial intelligence that enables computers to see and identify images, processing them as humans would. Using images from cameras and videos, deep learning models enable machines to accurately identify and classify the objects. Computer vision can be confused with image processing. However, computer vision is a more high-level process. It deals with the analysis of an image. In the CV process, the input is an image while the output is the interpretation of an image.