Artificial Intelligence Computer Vision 2

Question 1

What is 'transfer learning' typically used for in computer vision applications?

Accepted Answer

Starting with weights from a model pre-trained on ImageNet and fine-tuning on a smaller domain-specific dataset

Answer

Transfer learning leverages rich feature representations learned from large image datasets (e.g., ImageNet) and adapts them to new tasks with less data and compute.

Question 2

What does the Intersection over Union (IoU) metric measure in object detection?

Accepted Answer

The overlap between predicted and ground-truth bounding boxes divided by their union

Answer

IoU measures how well a predicted bounding box overlaps the ground-truth box; a higher IoU (closer to 1.0) indicates a more accurate localization.

Question 3

Which technique allows a network to locate the image regions most responsible for a classification decision?

Accepted Answer

Grad-CAM (Gradient-weighted Class Activation Mapping)

Answer

Grad-CAM uses gradients of the target class score flowing into the final convolutional layer to produce a heatmap highlighting discriminative image regions.

Question 4

What is 'optical flow' in computer vision?

Accepted Answer

The pattern of apparent motion of objects between consecutive video frames

Answer

Optical flow estimates the vector field of pixel motion between frames, used for video analysis, action recognition, and object tracking.

Question 5

What is 'non-maximum suppression' (NMS) used for in object detection?

Accepted Answer

Eliminating redundant overlapping bounding boxes by keeping only the highest-confidence detection per object

Answer

NMS suppresses duplicate detections by discarding bounding boxes that overlap significantly with a higher-scoring box, ensuring each object has one final detection.

Artificial Intelligence Practice Test

Artificial Intelligence Practice Test

Artificial Intelligence Computer Vision 2