Computer Vision Assessment Test Q1 What is the smallest unit of an image? 1 sq. mm DPI Pixel None of the above Q2 How can we change the resolution of an image from 1280 x 720 pixel to 720 x 480 pixel? Image Cropping Image Resizing Image Skewing None of the above Q3 Which of the following combination of colours can be used to represent almost any colour in electronic systems? Yellow-Red-Green Blue-White-Green Red-Yellow-White Green-Red-Blue Q4 Select the pixel matrix that is the correct representation of the following black and white image. (Pixel value can range from 0 to 255) Q5 Given below is an image of a dog surrounded by a bounding box. What are the coordinates of the points a and b in the image? a = (9, 2) and b = (16, 9) a = (2, 9) and b = (9, 21) a = (9, 21) and b = (9, 1.5) a = (9, 21) and b = (16, 1.5) Q6 Which evaluation metric can be used to solve an image classification problem? F1 score AUC-ROC score All of the above None of the above Q7 Facial Keypoint Detection is used in computer vision to detect key points on a human face. What is the nature of this task? It is a regression problem It is a classification problem It is a clustering problem Q8 Working on computer vision problems require huge amount of image data. However, when we have insufficient data, we use image augmentation to create more images from the existing images. Which of the following methods can be used to perform image augmentation? Image rotation Change colours of the image Change contrast and brightness All of the above Q9 Which machine learning algorithm can be used to perform image classification task? Logistic Regression Support Vector Machine Decision Tree All of the above Q10 The task of image classification is performed by extracting features from the images and feeding them to a predictive model. Let’s say you are working on an image classification task and you want to predict whether an image contains a car or not. Now from the three images below, which will require the least amount of computation for feature extraction? Image 1 Image 2 Image 3 Thank you for taking our survey. Name:Email:Phone:« Back Next »
