Artificial intelligence is a term we hear a lot in recent years. One of the most popular AI applications is image recognition.
Image recognition is a technology that uses deep learning to recognize visual elements in a photo. By being able to use large databases and seeing patterns, Image Recognition can “understand” photos and create appropriate categories for them.
Below, I have outlined the top six image recognition applications that are widely used today.
Examples of AI Image Recognition Applications
Visual search
Visual product search connects online and offline shopping stronger together. Visual search powered by neural networks enables companies to offer a unique customer experience.
Now, customers can download an app of a brand, go to the physical store, and learn all the details about particular products just by taking a picture of them. What’s more, they can order them easily and instantly.
You can also streamline your online shopping. Neural networks can describe the item in the photo, analyze characteristics such as material, color, style, and showcase similar products in stock.
Automated Image Organization
Perhaps the most popular and used image recognition application is personal photo organization. Each of us collects hundreds of photos on a mobile phone, it is difficult to organize them according to a specific topic.
Image recognition offers a solution – photo organization applications. Typically, such applications offer storage space, image categorization supported by machine learning engines, and more precise search functions. Your photo collection will be automatically grouped by theme based on the identified patterns.
Logo detection
Usually, companies from the very beginning work on building the desired brand image. In today’s world, social media has a huge impact on how potential customers perceive your business.
Therefore, companies benefit greatly from having reliable information about how customers interact with the brand, what they say about it on the Internet, and how they judge it. In conclusion – social listening.
Recently, we have been observing the development in this area of the so-called “Visual Listening”.
This is where AI-based image recognition comes in along with logo detection. Companies can now analyze visual data looking for the one that is related to their brand. As social media today is inundated with images, more often than words, image recognition can gather valuable information about brand awareness.
Based on this information, companies can calculate ROI (for example from sponsored events) and detect misuse of their logo.
Stock Websites
Stock websites are platforms where artists can sell their photos and video materials so that marketers can use them in their content. Stock platforms can benefit greatly from using image recognition.
Contributors have a problem with tagging visual materials. This is a frustrating task because it is often time-consuming and repetitive, but at the same time crucial – only materials with the appropriate keyword assignment will be easily indexed and discovered by potential buyers.
Image recognition offers innovative tools to automatically suggest keywords. This AI-based solution is of great help to both artists and customers.
Medical image data analysis
With the help of deep learning models, artificial intelligence can create software to help radiologists interpret huge amounts of medical images.
The AI software can analyze, among other things:
- computed tomography,
- ultrasound scans,
- magnetic resonance imaging,
- x-rays.
Every day, doctors have to examine hundreds of medical images, which are the main type of medical data. AI-based technologies such as image recognition can support clinicians in their decision-making process by identifying critical patients.
In addition, diagnostics using deep learning software are very accurate – radiologists gain a reliable partner in the analysis of medical images. Now doctors can make informed decisions and prioritize their tasks.
Facial recognition at the airport
Airlines are among the industries that make extensive use of facial recognition technology. The main goal is to streamline boarding and check-in processes to make them easier and faster for both staff and passengers. By saving time, airlines can reduce their costs.
One of the innovations we may already experience is face scans at the boarding gates. Cameras scan passengers’ faces and compare them with images stored in the databases of border control authorities to verify their identity. Usually, facial scans are compared to photos on visas, ID cards, etc. Tickets and passports are still required to pass security, but this may change in the near future.
To Sum Up
Image recognition driven by AI technology has a lot to offer to companies operating in different industries. If you happen to be an entrepreneur, currently looking for growth opportunities, check out different artificial intelligence services.
Now take a moment to consider how many image recognition applications you use daily without noticing it.