Computer Vision
Computer Vision is the science and technology of machines that see. Computer Vision is held as a scientific discipline which concerns theory and technology for building artificial intelligence systems which gather information from images and multi-dimensional data.
Artificial Intelligence largely deals with careful planning and deliberation for systems which can perform mechanical actions; such as moving hardware within production lines. This form of intelligent data processing typically requires input data which can only be provided by a Computer Vision system, acting as a vision sensor and producing high-level information about the working environment.


Computer Vision is reaching an advanced stage, and is being used across daily life and business operations to conduct multiple functions such as face recognition, identification, verification, emotion analysis, and crowd analytics. Further uses include: warning drivers of animals on the road and pinpointing issues in x-rays.
Gaming has also seen Computer Vision being integrated into its systems such as the Xbox Kinect and PlayStation Eye which “sees” and analyses our movement. Evidently, Computer Vision is being implemented into our everyday lives to enhance the entertainment industry, security, autonomy and provide us with invaluable statistics.
Computer Vision is now being used to scan social media platforms to find relevant images which would not be available through traditional searches. The technology itself is far more complex and intuitive, and just like the aforementioned tasks, it requires more than just image recognition, but also semantic big data and analysis.
It has taken computer scientists almost 80 years to get to where we are today and with Deep Learning, Data Modelling and Computer Vision, we are continuously refining the Artificial Intelligence landscape.
How can I use it?
Computer Vision revolves around the automatic extraction, analysis and understanding of useful information from a single or sequence of images. Find out how you can use the development of a theoretical and algorithmic basis to achieve an autonomous visual understanding in gaining a competetive advantage.
Computer Vision In Industry
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