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AI Technical Direction: Computer Vision

Latest reply: Nov 21, 2021 14:24:13 466 4 5 0 0

Hello friends. Artificial Intelligence has five main technical direction areas. These are Computer vision, Speech recognition, Natural Language recognition, Planning decision system and Big Data Analysis. In this post I will be sharing with you an insight about Computer Vision. Hope you will learn something. Please feel free to comment and I’m very open for further discussion. Enjoy.



computer vision


Overview of Computer Vision

Computer vision is a subfield of Artificial Intelligence that is responsible for making or teaching computers to see, observe and understand the visual world of digital images and videos. The end goals of computer vision include:


  • Understand the content of digital images or videos through mimicking human vision capabilities

  • Registration of different views of the same scene

  • Searching for digital images by their respective content.


Top Factors Contributing to Computer Vision

·         Through technologies such as virtualization and computing frameworks like cloud computing, computing power has become more affordable and easily accessible.

·         Mobile development technologies with built-in cameras have saturated the world with videos and photos.

·         Some top notch algorithms like Convolutional Neural Networks can be implemented to take advantage of the modern hardware and software capabilities.

·         Modern enhanced hardware specifically designed for Computer Vision and Analysis is now more widely available.

·         Collaboration between expert from different fields has also been aiding to the development of Computer Vision.


Common Computer Vision Tasks

  • Image Classification – this area involves training machine learning models to classify images based on their related content. For example, in a traffic monitoring solution, you use an Image classification model to classify images based on the type of vehicle they contain such as a bus or bike.

  •   Image Analysis – with image analysis, you can create a solution that integrate machine learning models and advanced image analysis techniques that can extract information from images and provide a summary of what is shown on the image

  • Semantic Segmentation – Is an advanced machine learning model technique in which individual pixels in an image are classified according to the object to which they belong

  • Object Detection – with object detection, machine learning models are trained to classify individual objects within an image and identify their position using a box. For example, in a traffic monitoring solution, we can use object detection to identify the location of different classes of vehicles.

  •   Optical Character Recognition – Is a technique used for reading and detecting text in digital images. You can use it to extract information from scanned documents like letters and forms.

  • Face Detection, Analysis and Recognition – Is a form of object detection that can locate human faces within an image.



Huawei Computer Vision Artificial Intelligence Solution with HiLens

Huawei HiLens is a multimodal AI development platform featuring a device-cloud synergy. It provides an easy-to-use framework, out-of-the-box development environments, a cloud-based management console, and an AI skill market (a skill can be seen as an AI application ready to run on a camera or another end user device, and it consists of a model and logic code). With Huawei HiLens, you can easily develop and deploy visual and auditory AI applications online, and manage a multitude of connected compute devices. (source: https://huaweicloud.com)

 

Computer Vision Application Scenarios

  • Retailers can use computer vision to enhance the shopping experience, increase loss prevention and detect out-of-stock shelves. Computer vision is already helping customers in checkout more quickly, aiding using self-checkout machines or combining with machine learning to alleviate the checkout process completely.

 

  • Public sector agencies use computer vision to better understand the physical condition of assets under their control, including equipment and infrastructure. Computer vision can help agencies perform predictive maintenance by analysing equipment and infrastructure images to make better decisions on which of these require maintenance.


Conclusion

This is a basic introduction to computer vision which is a subfield of Artificial Intelligence. Computer vision make use of Machine learning and deep learning algorithms and principles.

Please feel free to add more on this topic and also your comments and suggestions are welcome. Thank you.

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Chanbora
Created Oct 28, 2021 04:30:49

Nice
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Unicef
MVE Created Nov 16, 2021 15:04:48

Good share thanks
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thisu
Created Nov 16, 2021 15:10:42

Thanks for sharing
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user_4358465
Created Nov 21, 2021 14:24:13

Good Post. A nice summary on the topic
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