HOTSPOT - For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point. Hot Area:
In which two scenarios can you use the Form Recognizer service? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.
You need to make the press releases of your company available in a range of languages. Which service should you use?
A. Translator Text
B. Text Analytics
C. Speech
D. Language Understanding (LUIS)
Translator is a cloud-based machine translation service you can use to translate text in near real-time through a simple REST API call. The service uses modern neural machine translation technology and offers statistical machine translation technology. Custom Translator is an extension of Translator, which allows you to build neural translation systems. Reference: https://docs.microsoft.com/en-us/azure/cognitive-services/translator/
Question 85
HOTSPOT - You have a database that contains a list of employees and their photos. You are tagging new photos of the employees. For each of the following statements select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point. Hot Area:
You need to develop a mobile app for employees to scan and store their expenses while travelling. Which type of computer vision should you use?
A. semantic segmentation
B. image classification
C. object detection
D. optical character recognition (OCR)
Azure's Computer Vision API includes Optical Character Recognition (OCR) capabilities that extract printed or handwritten text from images. You can extract text from images, such as photos of license plates or containers with serial numbers, as well as from documents - invoices, bills, financial reports, articles, and more. Reference: https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/concept-recognizing-text
Question 87
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?
A. object detection
B. semantic segmentation
C. optical character recognition (OCR)
D. image classification
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
Question 88
HOTSPOT - For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point. Hot Area:
Box 1: Yes - Custom Vision functionality can be divided into two features. Image classification applies one or more labels to an image. Object detection is similar, but it also returns the coordinates in the image where the applied label(s) can be found. Box 2: Yes - The Custom Vision service uses a machine learning algorithm to analyze images. You, the developer, submit groups of images that feature and lack the characteristics in question. You label the images yourself at the time of submission. Then, the algorithm trains to this data and calculates its own accuracy by testing itself on those same images. Box 3: No - Custom Vision service can be used only on graphic files. Reference: https://docs.microsoft.com/en-us/azure/cognitive-services/Custom-Vision-Service/overview
Question 89
You have a bot that identifies the brand names of products in images of supermarket shelves. Which service does the bot use?
A. AI enrichment for Azure Search capabilities
B. Computer Vision Image Analysis capabilities
C. Custom Vision Image Classification capabilities
D. Language Understanding capabilities
Question 90
DRAG DROP - Match the types of machine learning to the appropriate scenarios. To answer, drag the appropriate machine learning type from the column on the left to its scenario on the right. Each machine learning type may be used once, more than once, or not at all. NOTE: Each correct selection is worth one point. Select and Place:
Box 1: Image classification - Image classification is a supervised learning problem: define a set of target classes (objects to identify in images), and train a model to recognize them using labeled example photos. Box 2: Object detection - Object detection is a computer vision problem. While closely related to image classification, object detection performs image classification at a more granular scale. Object detection both locates and categorizes entities within images. Box 3: Semantic Segmentation - Semantic segmentation achieves fine-grained inference by making dense predictions inferring labels for every pixel, so that each pixel is labeled with the class of its enclosing object ore region. Reference: https://developers.google.com/machine-learning/practica/image-classification https://docs.microsoft.com/en-us/dotnet/machine-learning/tutorials/object-detection-model-builder https://nanonets.com/blog/how-to-do-semantic-segmentation-using-deep-learning/
