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Machine learning methods and systems for managing retail store processes involving cashier-less transactions

机译:机器学习方法和系统,用于管理涉及无现金交易的零售商店流程

摘要

Devices, systems, and method are provided for identifying actions in a retail store. One method includes sampling a shopping environment using one or more sensors. The method includes receiving output of the sampling as feature inputs to a machine learning classifier model to derive one or more labels characterizing a state of an item. At least one processing entity associated with the retail store detects the state of the item to change from one as item taken to one as item returned, and sensor data from said one or more sensors characterizing the item as having been returned to a wrong location in the retail store. In further embodiments, items taken are added to a user's electronic shopping cart to enable processing of a cashier-less transaction.
机译:提供了用于识别零售商店中的动作的设备,系统和方法。一种方法包括使用一个或多个传感器对购物环境进行采样。该方法包括接收采样的输出作为对机器学习分类器模型的特征输入,以导出表征项目状态的一个或多个标签。与零售商店相关联的至少一个处理实体检测该物品的状态,以从一件物品变成一件物品而返回到一件物品返回,并且来自所述一个或多个传感器的传感器数据将物品表征为已经被错误地返回到错误的位置。零售商店。在其他实施例中,将所取物品添加到用户的电子购物车中,以使得能够处理无收银员的交易。

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