Should this be YYY?
With Azure Custom Vision, you can create and train a custom object detection model that is specific to your needs. This means that you can train the model to identify multiple types of damaged products in an image, and the model can be refined and improved over time as more data becomes available.
It should be Y, Y, Y... That statement is True.
Object detection is a computer vision task that involves identifying and locating objects within an image or video. It can be used to detect multiple types of objects in an image, including damaged products.
There are several object detection algorithms and techniques, such as YOLO (You Only Look Once), SSD (Single Shot Detector), and RCNN (Region-based Convolutional Neural Network). These algorithms can be trained to detect various types of objects, including damaged products, in images.
For example, a machine learning model trained on images of damaged products can be used to detect and locate defects in manufacturing lines, quality control processes, or customer returns.
Therefore, the statement "Object detection can identify multiple types of damaged products in an image" is true, as it's a computer vision task that can be used for this purpose.
The answer should be YYY! This is definitely a custom vision scenario, and just like object detection it can identify multiple objects at the same time, so why would that limitation exist here?
Should be YYY
Here are the statements with their corresponding answers:
Object detection can identify the location of a damaged product in an image.
True: Object detection can be used to locate and outline the position of a specific object or region in an image, including a damaged product.
Object detection can identify multiple instances of a damaged product in an image.
True: Object detection is capable of identifying and locating multiple instances of a specified object, such as multiple damaged products in an image.
Object detection can identify multiple types of damaged products in an image.
True: Object detection can identify and classify different types of objects, including multiple types of damaged products in an image, if it has been trained to do so.
YYY is the answer.
https://learn.microsoft.com/en-us/azure/cognitive-services/computer-vision/concept-object-detection
Object detection is similar to tagging, but the API returns the bounding box coordinates (in pixels) for each object found in the image. For example, if an image contains a dog, cat and person, the Detect operation will list those objects 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 object in an image.
The third question is a bit interpretable. The answer is correct if they are different types of products belonging to the same category. Sort of like asking computer vision to identify the breed of an object called a cat. It won't be able to. If, on the other hand, different types meant the category of the object then the answer would become Yes.
I honestly feel that the answer is correct although the question could be better asked.
I correct my previous answer. The question mentions Object Detection in general, not referring to Computer Vision or Custom Vision. So because with Custom Vision you can train the model you can also allow it to recognize different types of damaged products
YYN - answer is correct.
Limitations: Objects are not differentiated by brand or product names (different types of sodas on a store shelf, for example). However, you can get brand information from an image by using the Brand detection feature.
Whoever uploaded the last batch of questions needs to check their work a bit better
upvoted 3 times
...
Log in to ExamTopics
Sign in:
Community vote distribution
A (35%)
C (25%)
B (20%)
Other
Most Voted
A voting comment increases the vote count for the chosen answer by one.
Upvoting a comment with a selected answer will also increase the vote count towards that answer by one.
So if you see a comment that you already agree with, you can upvote it instead of posting a new comment.
jordymsft
Highly Voted 2 years agordemontis
1 year, 8 months agommmmmnm
Most Recent 1 month, 1 week ago[Removed]
8 months, 1 week agohenryphchan
9 months agoCADMAN
1 year, 1 month agoIdontcareanymore
1 year, 2 months agoIdontcareanymore
1 year, 2 months agokd333200
1 year, 4 months agoschlaumeier
1 year, 4 months agoCertification_Champs
1 year, 4 months agogggtang
1 year, 5 months agozellck
1 year, 8 months agordemontis
1 year, 9 months agordemontis
1 year, 8 months agoaru25
1 year, 10 months agoXtraWest
1 year, 11 months agoXtraWest
1 year, 11 months agojits1984
1 year, 11 months agoshanidad
1 year, 11 months ago