By Pascal Bornet – Applications of computer vision in a physical environment include robots recognizing objects and self-driving cars interpreting signs and road markings. In a digital environment, computer vision is used for intelligent character recognition (ICR), which can digitize and interpret documents. Finally, computer vision can automate the analysis of images and videos. This has a vast range of applications, including medical diagnostics, business process documentation, biometrics and retail store automation, such as Amazon Go.

As businesses began considering how to adopt computer vision, they should understand that a large amount of training data may be needed, especially for applications like medical diagnostics or biometrics. The technology behind Amazon Go is also still very expensive and out of the reach of most small and medium enterprises.

Execution involves actually doing things — accomplishing tasks in digital environments. The execution capability acts as a glue to connect the other capabilities together in a streamlined way. For example, with the help of the language capability, it can collect sales data using the vision or language capabilities, automatically convey the data to the thinking and learning capability for analysis and compile and send out a report about the findings.

The key technologies supporting the execution capability are smart workflow, low-code platforms and robotic process automation (RPA). Smart workflow platforms help to automate predefined standard processes. Low-code platforms allow business users without coding skills to develop automated programs. RPA is used to automate any tasks that a human can do on a computer, such as opening applications, clicking menu items, entering text or copying and pasting. It learns by recording the actions of the human user and automating them.  Read On: