Which of the following examples accurately demonstrates the correct usage of Al Computer Vision
features in a UiPath project?
A. Employing Al Computer Vision to identify and interact with Ul elements in a remote desktop
application with low quality or scaling issues.
B. Utilizing Al Computer Vision to train a custom machine learning model to recognize specific
patterns in data.
C. Using Al Computer Vision to extract plain text from a scanned PDF document and store the output
in a string variable.
D. Applying Al Computer Vision to perform sentiment analysis on a provided text string and
displaying the result
Given what’s written in the documentation it’s A.
The Computer Vision activities contain refactored fundamental UI Automation activities such as Click, Type Into, or Get Text. The main difference between the Computer Vision activities and their classic counterparts is their usage of the Computer Vision neural network developed in-house by our Machine Learning department. The neural network is able to identify UI elements such as buttons, text input fields, or check boxes without the use of selectors.
Created mainly for automation in virtual desktop environments, such as Citrix machines, these activities bypass the issue of non-existent or unreliable selectors, as they send images of the window you are automating to the neural network, where it is analyzed and all UI elements are identified and labeled according to what they are. Smart anchors are used to pinpoint the exact location of the UI element you are interacting with, ensuring the action you intend to perform is successful.
This is taken directly from: Activities - Computer Vision activities