AI, NLG, and Machine Learning

What Is Computer Vision Technology?

Computer vision technology, a field of artificial intelligence (AI) in which computers are trained to understand visuals, is rapidly advancing as machine learning continues to evolve. Find out how computer vision and image processing technologies are transforming the future of AI.

By Mariana Ranzahuer
August 11, 2020

Over the years, we’ve seen a shift in the transformation of machine deep learning, along with advances in computer science, allowing new technologies to improve how they capture, understand, and interpret data.

At its core, computer vision technology, a field of artificial intelligence (AI) in which computers are trained to understand visuals, has become one of the most promising areas of AI and computer science and has been of significant interest to researchers in recent years.

The history of computer vision and image processing

Back in the 1960s, during the early days of this technology, the ultimate intention was to create a machine that could be as intelligent as a human being. Later, the goal transformed into the ability to ask computers what they could see, automating the processes of image recognition and image analysis. This kind of technology revolutionized many manual processes, including X-rays, MRIs, and high-resolution photography.

Fast forward to 2010, when the technology had its true breakout moment, thanks to ImageNet Challenge, an annual competition to see which algorithms could identify objects in a dataset's images with the lowest error rate.

As we saw this evolution, we also saw the rise of algorithms in solving individual tasks and, therefore, their improvement at doing a job based on constant repetition.

The rise of computer vision in AI

The transformation of this technology has shown that content is as important as the ability to transform visuals in a readable way for humans. Because this technology is powered by deep learning algorithms that use neural networks, it’s not only able to recognize—and break down—the information contained within an image but it can also memorize certain patterns and classifications that help to make the overall technology better over time. Certain patterns include image components, such as color scales, contours, pixels, and more.

As the AI system becomes better at every task iteration, more and more industries are benefiting from it. Computer vision technology is being used or tested in a number of fields, including image captioning, facial recognition, self-driving cars, healthcare, manufacturing, and many more.

The benefits of computer vision

Computer vision has propelled many businesses by automating tasks beyond the need for human intervention, so the technology offers significant benefits, including:

  • Simplified processes. By carrying out monotonous and repetitive tasks at a faster rate, this technology simplifies daily business processes.
  • Reliability. Computers offer capabilities that humans can’t. For example, computers never get tired, and they can offer reliable solutions—at any time of the day.
  • Accuracy. These systems commit few mistakes, unlike humans, thereby increasing the quality and accuracy of any process.
  • Diverse usage. The technology ranges from industry to industry and can accompany many of the activities performed within a company. This can help reduce costs associated with continually training new staff.
  • Reduction of costs. With machines taking on a number of tedious tasks and eliminating many errors, companies can save money that they might otherwise spend on fixing flawed processes and products.

    • With similarly impressive feats by AI and with the increasing presence of computer vision technology in various industries, the future of the technology appears to be full of promising outcomes. As we continue to see the growth of machine learning, businesses appreciate the value offered by these developments. In the near future, we expect to see the widespread adoption of other visual tasks, such as image classification, object recognition, and image segmentation, performing at a high degree of precision and at a low cost, which could offer seemingly limitless possibilities for our daily lives.