Exam AI-102 topic 2 question 8 discussion

The anwser is correct Create a project Upload and tag images Train a classifier model https://learn.microsoft.com/en-us/azure/cognitive-services/custom-vision-service/quickstarts/image-classification?tabs=visual-studio&pivots=programming-language-csharp For Type of model https://azure.microsoft.com/en-us/use-cases/defect-detection-with-image-analysis/

The choice between Object Detection and Classification depends on the nature of your defect detection problem in the production line components. Here are some considerations: Classification: You use classification when your goal is to determine whether a component is defective or non-defective. In this case, the Custom Vision model will be trained to classify the entire image as "good" or "defective." Classification is suitable if you want a binary answer. Object Detection: You use object detection when you want to identify and locate specific defects or objects within an image. This is useful if you have multiple defect classes or if you want to identify the exact location of defects within a component. So, if you only need to distinguish between good and defective components, classification may suffice. However, if you need to identify and locate specific defects within components, you should opt for object detection. The choice depends on the complexity of your use case and the level of detail you want to extract from the images. (Chat GPT) Honestly I think Classifier is more appropriate in this case

Got a similar one in Oct 2024, some wording change from memory.

Answer is correct, it is a classifier since custom vision only builds an image classifier, detection is part of normal vision.

Got this in the exam, Jun 2024.

1. Create a project 2. Upload and tag images 3. Train a classifier model

1. Create a project 2. Upload and tag images 3. Train a classifier model

Final Answer: Create a project Upload and tag images Train a classifier model

I think the key is recognizing it's a production line. That means the same component is coming down the line. Then there are other lines producing other components. Classification would be best suited for that scenario. If we were looking at an image that might have many different components in one image and want to find the location of different faults, then object would be more appropriate.

It's a classifier model because it's not detecting whether they objects are there or not, it's classifying them as faulty or not

I would pick object detection. Custom Vision functionality can be divided into two features. Image classification applies one or more labels to an entire image. Object detection is similar, but it returns the coordinates in the image where the applied label(s) can be found. If I were the users, I would certainly want know where the faults are located to make sure and have a second look and it’s quite useless by just telling me there are something wrong but can’t tell you where they are as I need to do extra work to find them!

Yes the anwser is correct Create a project Upload and tags images Train the classifier model https://learn.microsoft.com/en-us/azure/cognitive-services/custom-vision-service/quickstarts/image-classification?tabs=visual-studio&pivots=programming-language-csharp and for type of model https://azure.microsoft.com/en-us/use-cases/defect-detection-with-image-analysis/

Correct answer should be: Create Upload & Tag Train the object detection model The question was to help "detect" common faults. Detection means where the fault actually is in the image.

Create Upload Train the classifier

Quite confusing on the questions, since Object Detection technically can be correct IMO

Correct