HOTSPOT - (Topic 5)
Select the answer that correctly completes the sentence.

Solution:


Does this meet the goal?

1. A. Yes
2. B. No

Correct Answer: A

- (Topic 5)
Which Computer Vision feature can you use to generate automatic captions for digital photographs?

1. A. Recognize text.
2. B. Describe the images.
3. C. Identify the areas of interest.
4. D. Detect objects.

Correct Answer: B

HOTSPOT - (Topic 5)
correctly completes the sentence.

Solution:


Does this meet the goal?

1. A. Yes
2. B. No

Correct Answer: A

HOTSPOT - (Topic 5)
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Solution:


Does this meet the goal?

1. A. Yes
2. B. No

Correct Answer: A

- (Topic 3)
You send an image to a Computer Vision API and receive back the annotated image shown in the exhibit.

Which type of computer vision was used?

1. A. object detection
2. B. semantic segmentation
3. C. optical character recognition (OCR)
4. D. image classification

Correct Answer: A
Object detection is similar to tagging, but the API returns the bounding box coordinates (in pixels) for each object found. For example, if an image contains a dog, cat and person, the Detect operation will list those objects together with their coordinates in the image. You can use this functionality to process the relationships between the objects in an image. It also lets you determine whether there are multiple instances of the same tag in an image.
The Detect API applies tags based on the objects or living things identified in the image. There is currently no formal relationship between the tagging taxonomy and the object detection taxonomy. At a conceptual level, the Detect API only finds objects and living things, while the Tag API can also include contextual terms like "indoor", which can't be localized with bounding boxes.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/concept-object- detection