Computer Vision deep Learning Interview Questions

Computer Vision deep Learning Interview Questions

Computer Vision deep Learning Interview Questions

Introduction  

Computer vision is an evergreen and every growing technological field which primarily deals with image construction and image analysis.  One of the most advanced features and applications of computer vision is artificial intelligence.  AI can be used anywhere because of its multiple uses and broad horizon of advancements can be done in any industrial sector.  As its popularity grows exponentially, the demand in AI engineers and technicians also growing day by day.  One of the core subjects of studying and developing AI would be computer vision.  Most of the Computer Vision deep Learning Interview Questions.

Today I am going to list out some of the important and frequently asked computer vision interview questions that you can expect!

 

What is computer vision?

As you can expect the most basic but must anticipated question from the HR would be what is computer vision?  Impress them with a proper and understanding definition with suitable example precisely.

Answer: Vision of humans can do magical phenomenon.  Likewise computer vision has improvised over the years and has completed ambitious goals for the humankind. Computer Vision deep Learning Interview Questions It plays main role in Virtual Reality and Augmented Reality.  Scanning documents by using mobile phones done by computer vision, QR code is the vital part of money transaction and it’s one of its applications, and also face detection or eye detection its done by computer vision.

For example Apple iphones are coming with advanced video shooting features every year.  Image capturing is the process done by computer vision and with each upgrades with iphones we can clearly see how this field has improved with many folds.

 

Grayscale Vs Color

This question can be asked as what is the purpose of grayscale or the difference between grayscale and color.

Answer: we might think if it would be better to replace grayscale and change everything into RGB because of the information we get.  But it might not be the case always.

Grayscale is very cheap compared to color and has high storage.  For example if CCTV has RGB instead of grayscale all the data arriving from the sources will take many years to analyze it.  So it would be a no.  For simple mechanical inspection one must remember analyzing the shape is what we need instead of color.  So most of the time its unnecessary.

 

What programming language does computer vision support?  

This is one of the common questions you can expect from the hiring managers.

Answer: computer vision is a versatile field which uses more than one language.  The programming languages such as Java, C, C++, Python, Prolog are widely used.  I use python for my computer vision related programs and also I prefer Java for as my second favorite.

 

What are computer vision libraries?

This question is being asked to test your fundamentals and your standards in the field.  Provide them a better example which needs to be a new one instead of an old timer.

Answer: computer vision libraries are set of mathematical functions which are being used directly for neural works.  It is a framework or toolbox which provides you with solutions for developers and data engineers.

For example, Caffe is a framework which deals with image processing and object recognition.  Caffe2 was released later after it’s predecessor success by facebook.

 

How can you do image processing?

It is a subject related question which can be asked to test your knowledge both on the subject and level of your technical skill.

Answer: During image processing we start with an image in one storage area and generate a new processed image in another storage area.  In practice these storage areas may either be in a special hardware unit called a frame store that is interfaced to the computer or they may be in the main memory of the computer or one of its discs.   Images are stored in image spaces like P, Q, R, etc.

 

What are the different types of filters available in open CV?

Answer: Filters are being used when the image has blurry or fizzy spots.  It works as replacing the pixels but valuing every pixel.

There are two types of filters:

  1. Linear filter

In linear filter there are three types which are, box filter, gauss filter and laplace filter.

  1. Non linear filter

In non linear filter there are divided into three types which are minimum filter, maximum filter and median filter.

How to read and display an image in OpenCV?  

Answer: To read and display an image in OpenCV, cv2.imread() method and cv2.imshow() method are being used respectively.

In cv2.imread() method it loads an image from specific file.  If it doesn’t have an image to begin with it will return as an empty matrix.  There are several specifications in this method such as cv2.IMREAD_COLOR, cv2.IMREAD_GRAYSCALE, cv2.IMREAD_UNCHANGED.

In cv2.imshow() method it displays the image with a name is Computer Vision deep Learning Interview Questions.

 

What is the difference between global and local descriptors?

Answer: In global descriptor it describes the image as a whole to generalize the entire object.  It includes features such as contour representation, shape descriptors and texture features.  Examples: Histogram Oriented Gradients, Shape Matrices etc.

In local descriptor it explains a patch within an image.  Multiple local descriptors are used to match an image but not all the descriptors are need to be matched.

Example: SIFT

 

How can you do object detection?

 This question can be asked with an example or just in a theoretical way.  But referring with an image will leave a better impression.

Answer: What we see in this image is what a computer is also see but extracting information from it is the complex part.  There are lot of information can a computer get from this single shot and it goes to a stage called image classification.  When computer goes under image classification the things it sees get divided and put it into different pre-set labels.

The basic information we get from this image are sky, mountain and river.  This is where computer vision undergoes second stage that is segmentation of image.  There are specific boundary lines which separates these three and computer break them into regions according to the space it occupied.

Then we can see an object that is a boat.  Whenever computer detects a object in an image it covers them within a box like we have in scanning features. Computer Vision deep Learning Interview Questions This stage is often called object detection where computer doesn’t gather any information what’s inside the box but simply put the object in it.

Then comes a complex part that is image reconstruction.  When we see this image we know that mountain is larger in size than the trees.  But computer never knows it beforehand.  So in image reconstruction phase the geometry of the object in the image provides the information to the computer vision.

Computer Vision deep Learning Interview Questions

Conclusion of Computer Vision deep Learning Interview Questions

Before going to an Computer Vision deep Learning Interview Questions related jobs remember to take notes on updated examples and new methods which are implemented recently.  It will boost your impression and yield you better results.

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