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COMPUTER VISION
Computer vision is a subset of AI that helps machines see and extract meaning from pixels in
an image. It is a field of AI that enables computers to see, identify, and process images to derive
meaningful information from these images, videos, and other visual inputs. Computer vision is
important and linked to AI as AI enabled systems must interpret what it sees just like human
vision and act accordingly.
The goal of computer vision is to train machines to see, process, and provide useful results
based on its observations within a very short time. This can only be possible if lots of data is
provided to it which can be analysed over and over until it detects distinctions and ultimately
recognises images. For example, to train a machine to recognise a bowl of fruits with different
fruits, it needs to analyse multiple images of different fruits. The AI will learn to differentiate
between them based on features like shape, colour, and texture, enabling it to identify each
fruit accurately in the future.
Human Vision System
bowl, oranges,
bananas, lemons,
peaches
Eye Brain
(sensing device responsible for capturing interpreting device responsible for
images of the environment) understanding the image content
Computer Vision System
bowl, oranges,
bananas, lemons,
peaches
Input Sensing device Interpreting device Output
The two technologies required to accomplish computer vision works are as follows:
Machine Learning (Deep Learning)
Convolutional Neural Network (CNN)
Machine learning enables a computer to understand the context of visual data by using
algorithmic models. To achieve this, enough data needs to be fed through the model so that the
computer can teach itself to recognise images.
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