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

CNNs use learnable convolutional filters to extract local spatial features at multiple scales, building hierarchical representations from edges to complex objects.

Question 2

What does 'image segmentation' mean in computer vision?

Accepted Answer

Assigning a class label to every pixel in the image

Answer

Image segmentation partitions an image into regions, assigning class labels to individual pixels for semantic segmentation or instance boundaries for instance segmentation.

Question 3

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

Accepted Answer

Object detection

Answer

Object detection identifies what objects are present and where they are by predicting class labels and bounding box coordinates for each detected instance.

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

Data augmentation artificially expands training data by applying label-preserving transformations, helping models become robust to variations in orientation, scale, and lighting.

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

Anchor boxes are a set of predefined bounding box shapes; the detector predicts offsets from these anchors to localize objects of different sizes and aspect ratios.

Artificial Intelligence Practice Test

Artificial Intelligence Practice Test

Artificial Intelligence Computer Vision