Store recognition
In many stores, managing inventory on the shelves is purely manual. Employees check the availability of products manually, count the balance. It is expensive and there is a high possibility of errors. Incorrect display or lack of goods leads to a decrease in sales.
Often, manufacturers make arrangements with retailers to display their merchandise so that their merchandise is in front of the customer's eyes and occupies as much space as possible. There is a need for constant audit, which leads to even greater expenses.
Often, manufacturers make arrangements with retailers to display their merchandise so that their merchandise is in front of the customer's eyes and occupies as much space as possible. There is a need for constant audit, which leads to even greater expenses.
Client
Shops, warehouses and food delivery services.
Product recognition neural networks help solve this problem. They can be used for inventory management, making it easier for retailers to keep track of products, ensuring they are in stock and replenishing stock. It is also better to analyze the behavior and preferences of consumers.
Neural networks can quickly and accurately recognize products by analyzing their characteristics, such as color, size, and shape. This helps stores reduce waste and improve the customer experience
Neural networks can quickly and accurately recognize products by analyzing their characteristics, such as color, size, and shape. This helps stores reduce waste and improve the customer experience
Solution
Examples of using
