Computer vision viva questions

What computer vision sees?
Computer vision is a field of artificial intelligence that trains computers to interpret and understand the visual world.
Using digital images from cameras and videos and deep learning models, machines can accurately identify and classify objects — and then react to what they “see.”.

What are the applications of computer vision?

Another significant application is in the field of autonomous vehicles.
Computer vision plays a critical role in enabling self-driving cars to perceive their surroundings, identify objects such as:

pedestrians

other vehicles

and traffic signs

and make informed decisions based on this information.

What Is Computer Vision?

A hiring manager may ask you this question to assess whether you have a basic understanding of AI imagining and self-learning.
This helps them understand your fundamental grasp of the work you might perform in the role.
You can answer by giving a definition with a focus on the utility of the method.
Example: "Computer vision is the scientific study.

What is the difference between computer vision and image processing?

Techniques in image processing include:

filtering

edge detection

noise reduction

and color transformations.
On the other hand, computer vision aims to enable machines to interpret and understand visual information from the world, similar to how humans perceive it.

What programming languages are used in computer vision?

Whether you've used all of them or not, you can list all of them to demonstrate your understanding of computer vision capabilities.
Example:

" Computer vision can use programming languages such as :

Java

C/C++

Prolog

Phython and LISP.

What's The Purpose of Grayscaling?

This is a question that interviewers might ask to further test how well you understand digital images.
To answer this question, you can give a definition and talk about how it applies to computer vision.
Example: "Grayscale is the range of whiteness to blackness of a digital image.
Programmers take an image that's in color and change it to grayscal.

Categories