AI in retail

In the modern field of artificial intelligence, the success of an algorithm depends on the quality of the data. As the importance of data in artificial intelligence models becomes increasingly prominent, it becomes crucial to collect and make full use of high-quality data. This article will help you better understand the core role of data in artificial intelligence programs.

As labor shortages intensify, the burden of stocking becomes a serious issue. Around the world, the adoption of robots to assist in retail environments has dramatically improved the efficiency and cost of high shelf replenishment stocking, a shift that has allowed people to better focus their time and energy on other tasks, such as helping customers with service and managing orders, a problem that has greatly improved.

However, such new ways of working need to be deployed in large numbers in more and more settings in order to get people used to them. Nexdata's AI training data is highly accurate and can help AI models perform rigorous testing tasks to ensure faster and more efficient execution, which will greatly help businesses thrive.

So, what benefits can robots provide under the retail industry?

Robots can work 24 hours a day without pay, without breaks or holidays, greatly reducing human capital and saving businesses more money.

Robots can perform many tasks that humans cannot perform, helping to relieve manual effort and better serve customers.

Robots can repeat boring tasks, providing humans with more time to provide quality customer service.

9,497 Images - OCR Data of 10 Types of Forms

Rectangular bounding boxes were adopted to annotate forms. The data can be used for tasks such as forms detection.

144,810 Images Multi-class Fashion Item Detection Data

In this dataset, 19,968 images of male and 124,842 images of female were included. The Fashion Items were divided into 4 parts based on the season (spring, autumn, summer and winter). In terms of annotation, rectangular bounding boxes were adopted to annotate fashion items. The data can be used for tasks such as fashion items detection, fashion recommendation and other tasks.

High-quality datasets are the cornerstone of the development of artificial intelligence technology. Whether it is current application or future development, the importance of datasets is unneglectable. With the in-depth application of AI in all walks of life, we have reason to believe by constant improving datasets, future intelligent system will become more efficient, smart and secure.