Artificial Intelligence Computer Vision

Question 1

What is the primary purpose of a convolutional neural network (CNN) in computer vision tasks?

Accepted Answer

To automatically learn hierarchical spatial features from images for recognition tasks

Answer

To translate images into text

Answer

To compress images for storage

Answer

To index images in a database

Question 2

What does 'image segmentation' mean in computer vision?

Accepted Answer

Assigning a class label to every pixel in the image

Answer

Dividing an image into a grid of equal tiles

Answer

Detecting and drawing bounding boxes around objects

Answer

Resizing an image to a standard resolution

Question 3

Which computer vision task outputs both a class label and a bounding box for each detected object?

Accepted Answer

Object detection

Answer

Image classification

Answer

Semantic segmentation

Answer

Optical flow estimation

Question 4

What does data augmentation in computer vision typically involve?

Accepted Answer

Applying random transformations like flips, rotations, and crops to training images to improve generalization

Answer

Collecting additional labeled images from the internet

Answer

Compressing training images to reduce disk usage

Answer

Converting images to grayscale before training

Question 5

What is the role of anchor boxes in object detection models like YOLO and Faster R-CNN?

Accepted Answer

They serve as pre-defined reference bounding boxes of various aspect ratios that the model adjusts to fit detected objects

Answer

They define the backbone CNN architecture

Answer

They store the training loss for each image

Answer

They control the color normalization of input images

Question 6

What is 'image classification' in computer vision?

Accepted Answer

Assigning a single label to an entire image based on its content

Answer

Segmenting an image into foreground and background

Answer

Detecting and tracking multiple objects across video frames

Answer

Estimating the 3D pose of objects in a scene