Disclosed herein are system, method, and computer program product embodiments for a dynamic symbol-based system for objects-of-interest (OOI) video analytics detection. Some embodiments include instantiating one or more symbolic objects associated with one or more real world rules, defining an area of interest, associating one or more CV functions with the one or more symbolic objects, and identifying one or more video sources for which to apply the one or more CV functions. Some embodiments further include executing the one or more CV functions associated with the one or more symbolic objects to process the one or more video sources.

Methods and systems for sharing image data between vehicles. The system includes an image sensor of a first vehicle configured to detect image data of an environment around the first vehicle as it traverses a road. The system also includes a transceiver of the first vehicle configured to communicate the detected image data. The system also includes a transceiver of a second vehicle configured to receive the detected image data. The system also includes a display screen of the second vehicle configured to display a view of the environment around the road based on the detected image data.

Methods and systems for sharing image data between vehicles. The system includes an image sensor of a first vehicle configured to detect image data of an environment around the first vehicle as it traverses a road. The system also includes a transceiver of the first vehicle configured to communicate the detected image data. The system also includes a transceiver of a second vehicle configured to receive the detected image data. The system also includes a display screen of the second vehicle configured to display a view of the environment around the road based on the detected image data.

Systems and methods for streamlined vehicle fueling and payment are provided. In an example, the present disclosure is directed to an automated, seamless payment system for use at a gas station or convenience store. In particular, the application is related to a payment system for use at a pay at pump arrangement that does not require the user to provide a specific payment method at the time of the gas pump use.

An image processing method includes: detecting repetition numbers of each image frame of an input image frame sequence, wherein the input image frame sequence includes sequentially inputted at least one first image frame and at least one second image frame, and image data of each first image frame is different from image data of each second image frame; determining a first lookup table according to a first repetition numbers of the at least one first image frame, wherein the first lookup table indicates a plurality of sets of compensation calculations; and using a first set of compensation calculations in the sets of compensation calculations to process the at least one first image frame according to a second repetition numbers of the at least one second image frame.

An image processing method includes: detecting repetition numbers of each image frame of an input image frame sequence, wherein the input image frame sequence includes sequentially inputted at least one first image frame and at least one second image frame, and image data of each first image frame is different from image data of each second image frame; determining a first lookup table according to a first repetition numbers of the at least one first image frame, wherein the first lookup table indicates a plurality of sets of compensation calculations; and using a first set of compensation calculations in the sets of compensation calculations to process the at least one first image frame according to a second repetition numbers of the at least one second image frame.

A card number recognition method and apparatus, a storage medium, and an electronic device are disclosed. The method includes: obtaining distribution format information of character bits of a card number sequence, where the distribution format information includes character bit spacing information of the card number sequence; recognizing a character sequence in a target image through a neural network model trained in advance, and obtaining character bit spacing information of the recognized character sequence; determining whether the character bit spacing information of the recognized character sequence is consistent with the character bit spacing information in the obtained distribution format information; and if the character bit spacing information of the character sequence is consistent with the character bit spacing information in the obtained distribution format information, determining that the recognized character sequence is target card numbers.

A method and an apparatus for pushing information are provided. The method may include: obtaining a prescription image presenting prescription information; recognizing the prescription image to obtain a recognition result inputting the recognition result into a pre-trained prescription image analyzing model to obtain the prescription information presented in the prescription image; and pushing information based on the prescription information.

A method and an apparatus for pushing information are provided. The method may include: obtaining a prescription image presenting prescription information; recognizing the prescription image to obtain a recognition result inputting the recognition result into a pre-trained prescription image analyzing model to obtain the prescription information presented in the prescription image; and pushing information based on the prescription information.

Systems and methods for generating targeted media content capture an image from an image capture device. The system may analyze the image to recognize a visual identifier for each entity in the image, each of which may have one or more group identifiers. The system may aggregate the group identifiers to identify the number of each group in the audience area and select media content to display to the audience based on the aggregate numbers of each group identified in the audience area. The system may also derive time restrictions for groups identified in the audience area to help optimize how groups traverse through one or more areas.