01 What is AI product recognition?

This is a bottle of fat water that will make you fat if you drink it. It is a high-end shopping mall with Gucci. It is an escape [ Beep——]... As a human being, when these images appear in front of you, you can immediately tell what it is and associate its various attributes.

What AI computer vision wants to do is the same thing - let computers understand the world like humans do.

As covered by the example just cited, currently, computer vision recognition technology is mainly used in three major fields: product recognition, scene recognition and human body recognition. Each field has its own subdivisions, such as the familiar face recognition technology, which is mostly used in security and marketing.

What we are going to talk about today is product identification technology that can be widely used and ubiquitous.

Different from face recognition, it is difficult to find similar appearance characteristics among different categories of products we come into contact with in daily life. At the same time, folding, deformation, and occlusion may occur, interfering with recognition. The challenge that AI product recognition needs to accept is to read the attribute information of the product including identity, category, quality, origin, specifications, trademark, and appearance through images indiscriminately. AI product recognition can be realized from macro, individual to micro recognition dimensions.

02 How to implement AI product recognition

So, how does computer vision “understand” images?

After the image is collected through cameras, X-ray machines and other equipment, the computer will first use a detection algorithm to accurately locate the location of the product in the image, then segment the image content of only this product, and extract Identify the image features of the product, which accurately describe the characteristics of the product including color, shape, and texture. Finally, the computer matches these features with the features of the product pictures stored in the database, judges the product information based on the degree of similarity, and outputs the results.

It sounds simple, but in fact this process involves many AI algorithms.

Take Malong Technology, which has always focused on the AI ??product recognition track, as an example. It requires research on computer vision core algorithms including weakly supervised learning, course learning, target tracking, object detection, etc.

On this basis, Malong Technology has created ProductAI?, a basic product recognition technology platform that integrates product image search, detection, classification, analysis, annotation, color analysis and text recognition, etc. Basic technology.

03 The application value of AI product recognition technology

When these basic product recognition technologies are combined with industries such as retail, textile and clothing, and quality inspection, it will bring about many enabling innovations. It can fully help B-side customers improve efficiency and reduce costs, while also optimizing the direct experience of C-side customers.

For example, unmanned retail smart containers can complete self-service settlement through AI product recognition; for example, supermarkets can use this technology to protect assets; for example, the fashion industry can use this technology to complete the management of show clothes. Big data analysis to grasp fashion trends; for example, the clothing industry can use AI technology to complete the measurement of clothing with millimeter accuracy...

04 The technical advantages of Malong Technology ProductAI

Then , what are the "must-have" advantages of Malong Technology's AI product identification technology?

Let’s go back to the example of people. Suppose there is an employee who is smart, responsive, broad-minded, and flexible. Do you think this is an employee worthy of reuse?

By analogy to Malong Technology's ProductAI product recognition technology, the core algorithm advantage of the weakly supervised learning algorithm CurriculumNet is its smart little head. The millisecond-level recognition speed ensures its work efficiency. It is in the product recognition track. Focusing on vertical data accumulation for nearly five years ensures its breadth of identification, and its flexible and multiple deployment methods can ensure response speed, stability and information security at the same time.

There are countless such "excellent employees" who work 24 hours a day and are active in all walks of life. Why worry about not improving efficiency?

Knowing "people" how to use them well is a magic weapon to improve combat effectiveness; similarly, applying the most advanced AI product identification technology to all walks of life can also help companies improve efficiency and reduce costs. In the future, from design, production, logistics to sales, AI product recognition technology has great potential.