Such projects include self-driving cars, drones, etc.Įdge computing has been gaining a lot of traction in the healthcare industry. Edge computing is especially popular for projects where real-time data processing is needed.

Even cloud architectures often need to be deployed on edge devices because of privacy, robustness, and performance. Computer vision projects are implementing edge computing architectures more and more because it solves the problems of network accessibility, bandwidth, and latency. The term edge computing refers to a technology attached to where the data is generated, i.e., at the edge of the architecture: it allows data to be processed and analyzed where (or closer to where) it is collected, instead of the cloud or a data center. Now that we covered where computer vision started and where it’s today, let’s jump into the “future” and reflect on some of the most promising trends in computer vision for 2022.Įdge is the new cloud. In particular, computer vision solutions constantly rely on both software and hardware evolution, where integrating new technologies becomes a challenging task. Another challenge that computer vision engineers face nowadays is the sustainable integration of open-source computer vision tools into their applications. However, it’s hard to imagine the amount of work it would take a computer to tackle something nearly similar. It takes a few seconds for people to recognize their friends in the images, even at different ages, and our capacity to remember and store faces for future recognition seems unlimited. This is mainly due to the fact that human vision itself is extremely complex and computer vision systems suffer by comparison. Though a lot of progress has been made on computer vision since the 1960s, it’s still a largely untapped field in terms of research and development. In this article, we’ll cover the foundations and trends in computer vision. So, given the abrupt evolution of computer vision, it’s important to investigate where it all started and where it’s going, especially when it comes to choosing the next computer vision project. Besides, due to the recent progress in computer vision, AI is now a necessity in various industries, such as education, healthcare, robotics, consumer electronics, retail, manufacturing, and more. The use cases of AI-enabled computer vision are nearly countless with the most popular being consumer drones as well as autonomous and semi-autonomous vehicles. According to Grand View Research, the global computer vision market size was valued at $11.32 billion in 2020 and is expected to expand at a compound annual growth rate of 7.3% from 2021 to 2028. Computer vision is among the most progressive and rapidly growing fields.

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