Abstract: An automated checkout system accesses an image of an item inside a shopping cart and a location of the shopping cart within a store. The automated checkout system identifies a set of candidate items located within a threshold distance of the location of the shopping cart based on an item map. The item map describes a location of each item within the store and the location of each candidate item corresponds to a location of the candidate item on the item map. The automated checkout system inputs visual features of the item extracted from the image to a machine-learning model to identify the item by determining a similarity score between the item and each candidate item of the set of candidate items. After identifying the item, the automated checkout system displays a list comprising the item and additional items within the shopping cart to a user.

Abstract: Disclosed herein relates to a self-checkout anti-theft vehicle system, comprising: a self-checkout vehicle having a plurality of sensors and components implemented thereon, the self-checkout vehicle being used by shoppers for storing selected merchandises in a retail environment; and a centralized computing device. The centralized computing device is configured to: obtain information related to each merchandise selected and placed into the self-checkout vehicle by a shopper by exchanging data with the plurality of sensors and components via a first communication network, identify each merchandise via a second, different communication network based at least upon the information obtained from the plurality of sensors and components, and process payment information of each merchandise.

Abstract: The application provides a brightness detection method, a computer device and a readable medium, where the brightness detection method includes: using each of display modules in a display module production line as a test module separately, where the test module is provided with a photosensitive sensor; obtaining a brightness algorithm formula of the photosensitive sensor of each of the test module; and performing, according to the brightness algorithm formula, ambient light detection by the photosensitive sensor.

Abstract: A method of performing a multimodal tasks by using a multimodal model that includes a text encoder and a vision encoder, may include obtaining a text feature from the query via the text encoder; obtaining an image feature from the one or more input images via the vision encoder; and outputting a response to the query based on similarity between the text feature and the image feature, wherein weights vectors of the text encoder and the vision encoder are pruned and shared according to a sharing vector and a pruning vector that are generated by a hypernetwork, and wherein the hypernetwork and the multimodal model are jointly trained to minimize at least one of a difference between the weight vectors in the text encoder and the vision encoder, a difference between the weight vectors in different layers of the text encoder, and a number of parameters in the multimodal model.

Abstract: This application relates to a rotating assembly, a foldable mechanism, and a foldable terminal, and relates to the field of terminal technologies. The rotating assembly includes a base, a rotating shaft, and a swing arm, where the base is provided with a rotating shaft through-hole and an arc-shaped first slideway, the first slideway and the rotating shaft through-hole communicate with each other, and axes thereof are parallel to each other; the rotating shaft is provided with an arc-shaped second slideway, an axis of the rotating shaft is parallel to an axis of the second slideway, the second slideway runs through the rotating shaft, and a radius of the second slideway is equal to that of the first slideway; the rotating shaft is located in the rotating shaft through-hole, the first slideway and the second slideway can be connected to each other to form a continuous slideway, and the swing arm is located in the continuous slideway and can slide in the continuous slideway.

Abstract: Disclosed herein relates to a self-checkout anti-theft vehicle system, comprising: a self-checkout vehicle having a plurality of sensors and components implemented thereon, the self-checkout vehicle being used by shoppers for storing selected merchandises in a retail environment; and a centralized computing device. The centralized computing device is configured to: obtain information related to each merchandise selected and placed into the self-checkout vehicle by a shopper by exchanging data with the plurality of sensors and components via a first communication network, identify each merchandise via a second, different communication network based at least upon the information obtained from the plurality of sensors and components, and process payment information of each merchandise.

Abstract: Disclosed is an apparatus and an operating method for deep denitrification and toxicity reduction of wastewater. The apparatus comprises a regulation tank, an aeration biofilter, an ozone reaction tank, an ozone generation and diffusion device, and a denitrification biofilter. By the coupling reaction treatment of microorganisms, ozone, electrolysis and denitrification, an effect of refractory organic contaminants and nitrate nitrogen removal, deep denitrification and toxicity reduction can be achieved.