2023 Computer Vision Trends to Follow

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Computer vision (CV) technology has been advancing at an astronomical rate in the past few years, and this technology is likely continue to grow in popularity in the years to come. With the CV market expected to expand to $9.62 billion according to Report Ocean, there are plenty of advantages and trends to follow in the coming years that organizations can leverage to their benefit. Here are some of the top threeCV trends to keep an eye on in 2023.

One trend to watch is the improvement of edge computing for CV devices. Many of the applications of computer vision rely on low latency data processing to deliver seamless user experiences, but in the past, edge devices like sensors and cameras have had limited computing power. Therefore, much of the processing has had to be done in the cloud. However, thanks to improved edge computing, CV applications can now run real-time data processing and analysis, which reduces energy and bandwidth consumption, and increases computation efficiency. Furthermore, thanks to advancements in NAND Flash technology, much more data can be stored on the edge devices, adding an additional layer of security.

The second factor to watch is the rise of no-code and low-code development to address the talent shortage holding back the development of computer vision applications. These intuitive graphical user interfaces and visual programming can enable non-experts to create and deploy CV applications, while allowing specialized talent to work on more complex problems. Apple, Google, and Clarifai have already started to develop and launch low-code platforms to help you launch your computer vision projects right away.

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Finally, data and user privacy is of utmost importance for companies today. Many organizations are realizing the importance of privacy and using this feature as a means of differentiating themselves from competitors. This is a particularly important factor for attracting Gen Z customers, who are very selective when it comes to data privacy. As a result, companies need to make sure that their data privacy and security practices are up to par and ensure that their computer vision applications are created with user privacy top of mind.

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