Back to Blog

Top 10 Computer Vision Applications - E-commerce, Banking and more.

Top 10 Computer Vision Applications - E-commerce, Banking, and moreComputer-vision-applications-3

The first step towards creating any successful AI project is learning what type of project you want to create.  If you are interested in machine learning implementation for your business, but don't know how to start, this article lists the top 10 computer vision applications in Businesses.

Computer vision is the ability of computers to 'see', process, and predict images and videos. Most business sectors have computer vision use-cases that are transforming the way their industries are run.

Computer vision has been adopted by most companies rapidly, and the demand for computer vision and similar technologies has been growing rapidly.  The ability to accurately solve problems rapidly, at a large scale, with lower costs is the primary reason for this rapid growth.

As computer power becomes cheaper, more accessible, and portable, we can expect an increasing number of computer vision applications for businesses in the near future.

Here is our top 10 list of applications of computer vision in business, focusing on different sectors:

Table of Contents

Computer vision applications in E-commerce

E-commerce is booming across the globe.  One of the  applications in e-commerce is automatic product categorization. When a new product is added to an e-commerce store, its attributes are automatically extracted using computer vision systems without the need for human intervention.  This automates the process of labeling every new item that a store wants to add, allowing products to go up on the virtual shelves and into consumers hands' faster.  

Computer vision applications in Banking

Forward-thinking banks are using computer vision for implementing KYC (Know your customer) processes.  This allows customers to open accounts using a selfie and a short video call. Computer vision technology is also used to identify customer emotions in order to deliver actionable insights for the purpose of personalizing banking services across multiple channels.  Increased customer satisfaction and ease of creating accounts have a direct impact on banks' revenues.

Computer vision applications in Healthcare

Computer vision algorithms in the healthcare industry are evolving at a rapid rate.  This growth has led to more accurate readings of MRI and CT scans, and is optimizing radiology procedures, allowing doctors, nurses, and other healthcare specialists help patients get their health back.

Computer vision applications in the Automotive industry

Most new cars have accident prevention technology. These systems rely on computer vision technology and they process the road, where the lanes are, if there are nearby vehicles or people nearby, and other surroundings to predict accidents, warn the driver, and in some cases, automatically break. Facial recognition systems can also alert the driver if he is about to sleep.

Computer vision applications in Insurance

Computer vision systems assist in the process of inspecting damaged property, and could soon replace people in this process. Taking a picture, and receiving a quote immediately is much faster than waiting for a person to inspect your goods.  This makes the process of making a claim could be automatic rather than taking days or weeks.  

Related: Download the checklist that lays out everything you should consider  before implementing a machine learning project or workflow →

Computer vision applications in Marketing

Social media platforms are a fountain of images and videos.   Up to 95 million photos and videos are uploaded to Facebook daily. Handling and processing such massive volumes of data manually is not possible. Computer vision can process images automatically, finding brand logos quickly, finding optimal color patterns for different targeted markets, and searching for the subject of pictures.  Computer vision can allow companies to cater towards targeted markets in a more personalized manner.  

Computer vision applications in Retail

Computer vision helps stores monitor customers' buying patterns in stores and helps the process of placing products on the shelves for easy discoverability - leading to more sales.  Amazon uses computer vision technology to automatically capture what people have bought in their store for an automated and easy shopping experience.

Computer vision applications in Manufacturing

In manufacturing, one application of computer vision is to perform predictive maintenance. Computer vision leads to reduced downtime in this case. Using images obtained through CCTV cameras, it is possible to predict the machine that is most likely to have a breakdown next. Therefore, necessary maintenance can be done and required spare parts be purchased. Other applications involve automated package inspection and reading barcodes.

Computer vision applications in Sports

In sports, computer vision can track the movement of players. More complex game analysis and insights are be generated in real time to help improve player and manager performance.  This improves game watching experience, accuracy of referees, and can lead to better player performance over time.

Computer vision applications in Logistics/ Supply chain

In logistics, computer vision is being used to accurately count and track inventory which leads to better accountability. This is also can be used to check the quality of packaging.  OCR (optimal character recognition)  is used to reading the text on the labels of packages.

Computer vision applications in Radiology

Computer vision can help radiologists to detect pneumonia with a much better accuracy percentage. Also, cancer can be detected much earlier with at an earlier stage saving precious lives.

pneumonia detection chest xrays

Computer vision applications in radiology

pneumonia machine learning detection

Computer vision application for detecting pneumonia in chest X Rays

If you would like to learn more about how to implement computer vision technology into your business, visit Skyl.ai.

how-to-ensure-that-your-machine-learning-project-is-successful

 

    

Comments