Due to the inherent complexities like determining object relationships and identifying multiple objects, image recognition has been a long-standing problem in the computer vision sector. But with rapid evolution in the Artificial Intelligence (AI) sector, machines now have better image identification, object detection, and image classification capabilities. Many industries are integrating AI-powered image recognition with their existing systems to boost AR applications, predict customer behavior, and much more.

One of the fascinating applications of AI has been in the retail industry, online and offline. Visual commerce has been registering incredible growth in the last few years, and now with the integration of AI, the impact of visual commerce is believed to grow even further in coming years. Image recognition is helping online and offline marketplaces gain valuable insights into the latest trends, expand customer reach, and improve the online shopping experience.

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How can AI Image Recognition Impact Online/Offline Marketplaces?

Image recognition can be described as the technology that can ascertain attributes and objects in images and videos. When combined with powerful technology like AI, image recognition can deliver exceptional results for online and offline marketplaces. Some of how AI image recognition can impact marketplaces are as follows: –

1. Search by image

Many customers wish to possess a product that their favorite celebrity uses but are unsure about the brand or where it is available. With AI image recognition, users can conduct an image search immediately and find out their desired products. eCommerce platforms can use image-based search as an extension to their software and enhance the chances of capturing the customer’s attention.

2. Augmented and Virtual Reality

Whether it be online or offline shopping, customers tend to get confused about how a product would look or work. AI image recognition helps AR software applications to integrate virtual content with reality. This allows the customers to experience how the product would work for them and if they should invest in it. Businesses can leverage this technology to showcase the utility of their products to customers.

 3. Identifying fakes

Fakes pose a challenge for online and offline customers and sellers. Many customers have bad experiences with fakes and are wary about investing their money in something they are unsure of. This is where AI-powered image recognition can come to the rescue. Logo recognition has become a norm in the eCommerce industry for detecting counterfeits. Logo recognition allows eCommerce platforms to discern fake logos from real logos. As s when a fake is identified, that item is removed from the site, and the seller is warned.

 4. Attribute Tagging

Most eCommerce platforms, especially fashion-related platforms, struggle to make customers make purchases. If the customers cannot find the required products in a few minutes, they will drop off after a few minutes due to frustration. This is where AI-based image recognition can help eCommerce platforms with attribute tagging. With this technology, platforms can generate product attributes automatically to help customers with their search. Product tags can include brand, color, size, fabric, type, discount, etc.

 5. Monitoring inappropriate content

AI-based image recognition can identify and remove inappropriate content from their platforms. Any products that do not match the written description or seem counterfeit can be flagged and removed from the platform immediately. This will help make the customer experience seamless and hassle-free.

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Some Well Known Image Recognition Platforms

AI Image Recognition tools are software powered by artificial intelligence to general a neural network. The data identified through AI Image Recognition tools can be useful for marketers in many ways. Here are the top AI Image Recognition platforms that are widely used by online and offline marketplaces: –

1. Microsoft Image Processing API

This tool from Microsoft leverage AI and machine learning to ascertain videos, images, and digital documents. This tool can identify up to 100 faces in an image with attributes like age, emotions, pose, sex, facial hair, or objectionable content. Microsoft Image Processing API can also identify common shapes, content descriptions, and digital handwriting.

2. Google Vision AI

Google Vision AI supports creating customized image models and using reverse image search. Google Vision AI allows the users to enter an image source and then explains its features for further analysis.

3. Amazon Rekognition

Amazon Rekognition is an extremely popular image recognition tool that can identify objects, faces, landscapes, and individuals in videos and images. This tool also supports searching and comparing features with the help of its neural network that can ascertain multiple objects in a given image.

The future of digital marketing will be determined by visual data. It is, therefore, extremely important for brands to leverage the available AI-powered image search tools to move ahead of the competition and establish a prominent online presence.