Why and When to Use Azure Computer Vision and Cognitive Services

As the number of business use cases it serves grows exponentially, the results across industry domains have been more than promising. In this post, we will be exploring Azure Computer Vision and Cognitive Services. We will discuss what these services are, when you should use them, and how they can benefit your business.

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What are Azure Computer Vision and Cognitive Services?

Azure Computer Vision and Cognitive Services are a suite of cloud-based services that allow developers to add image and video recognition capabilities to their applications. For example, software engineers can leverage resources like the Microsoft Learn module for Computer Vision and the Microsoft Docs page for Cognitive Services.

Computer Vision helps machines visually perceive the world around them using images, videos, and real-time camera inputs. Azure Computer Vision Services can identify and extract text from images, allowing for the automatic indexing of images for search and retrieval.

Cognitive Services also include a wide range of capabilities, such as facial recognition, emotion detection, and sentiment analysis. Both services are available in the Azure portal, and you can access them and customize them by adding a few lines of your own custom code.

What are the differences between Azure Computer Vision and Cognitive Services?

Azure Computer Vision and Cognitive Services are both part of Microsoft Azure’s Artificial Intelligence (AI) services.

However, there are some key differences between the two services.

Computer Vision offers image recognition and analysis, while Cognitive Services includes a broader range of AI services such as natural language processing, sentiment analysis, and facial recognition.

Cognitive Services is also a little more expensive, but it does offer more features. It’s worth considering both services when choosing the right one for your needs.

When should you use Azure Computer Vision?

You should use Azure Computer Vision when you need to extract text or data from an image or when you need to detect and identify objects or facial features in an image. Businesses can also use Azure Computer Vision to determine the sentiment of an image.

 

When should you use Azure Cognitive Service?

You can use Azure Cognitive Services when you need to interpret or understand the meaning of the text or when you need to recognize the natural language. Organizations can also use Azure Cognitive Services to predict outcomes or recommendations.

When it comes to Cognitive Services, there are a few key areas where they can be applied:

  • Understanding natural language: Businesses can leverage this feature to understand the text in images and videos better. It can also accurately process customer reviews and feedback.

 

  • Face detection and recognition: This is a popular authentication feature used to track customers and staff. This AI-powered tool can also accurately measure customer sentiment.

 

  • Object recognition: Object recognition is probably the most straightforward task for smart algorithms. This AI-powered feature is popular in retail as it can accurately identify products in images and videos.

 

  • Speech recognition: If you use Siri or Alexa, you know that speech recognition has come a long way in recent years. Today, companies can use it to transcribe speech into text, optimizing customer experiences.

 

The great thing about Azure Cognitive Services is that they’re all fully cloud-based and require no additional infrastructure or setup. You can get started with them in minutes, making them an excellent choice for businesses of all sizes.

Are you looking to leverage Computer Vision and other AI technologies for your software development project?

How do Azure Computer Vision and Cognitive Services work together?

Azure Computer Vision and Cognitive Services work together by first identifying the objects in an image and then classifying them according to their type. We can achieve this by leveraging a deep learning model that is constantly updating itself with new information.

Once it identifies the objects, the Cognitive Services part of the equation kicks in and provides additional information about each object. This can include data like name, description, category, and more.

You can also customize and build your own application leveraging Azure Computer Vision and Cognitive Services. For example, we at rinf.tech developed and deployed an advanced machine learning model, Vid.Supervisor. It runs over CCTV surveillance videos in a retail setting to identify and tag human behavior.

The primary objective was to reduce the amount of manpower used to complete this mundane and repetitive task. As AI takes on this task and successfully completes it, human staff only have to review and confirm the assigned tags.

Every time this happens, the accuracy of the algorithm will improve steadily. As staff don’t have to spend 90% of their time doing this monotonous task, they are free to focus their energy where it’s most needed

Key features of Vid.Supervisor include:

  • People detection (for staff tracking)
  • Facial recognition (extending the capabilities of people detection to track an individual’s activity over time)
  • Automatic creation of videos (for each individual)

 

Retailers who use Computer Vision and Cognitive Services powered tools like Vid.Supervisor can identify patterns and opportunities to rearrange their store, adapt floor staffing models, and (of course) boost productivity.

We can also leverage Azure AI-powered tools to detect and flag anomalies. You just have to set up one or more parameters to alert staff to potential violations. It can also support the fight against shoplifting in real-time.

For example, by measuring the weight and size of a product or through cameras and colors, AI will be able to flag products being put back but on the wrong shelf. You can implement such a real-time service with just a few lines of code.

Summary

Azure Computer Vision and Cognitive Services are probably the best examples of man and machine working together for maximum effect. Best of all, the more you use it, the more accurate the algorithm will be at detecting and tagging whatever you want it to.

While businesses can use Azure Computer Vision and Cognitive Services to improve the customer experience, there are other benefits as well.

Using these services effectively can improve worker productivity, assist with data analysis and mining, and help with fraud detection. By understanding when and how to use these services, businesses can improve their operations and return on investment.

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