A method includes: via a user interface of a hub device, receiving a first set of user credentials associated with a first operator, the hub device connected to a set of mobile devices; accessing a first operator schedule defining a first scheduled manufacturing operation and a first observer of the first scheduled manufacturing operation, the first observer characterized by a first set of observer credentials; detecting disconnection of a first mobile device in the set of mobile devices from the hub device, the first mobile device associated with a first device ID; in response to detecting disconnection of the first mobile device from the hub device, associating the first device ID with the first operator; and routing a first video feed from the first mobile device to the first observer based on the first device ID and the first set of observer credentials.

System and methods are disclosed for capturing license plate (LP) information of a vehicle in relative motion to a camera device. In one example, the camera system detects the LP in multiple frames, then aligns and geometrically rectifies the image of the LP by scaling, warping, rotating, and/or performing other functions on the images. The camera system may optimize capturing of the LP information by executing a temporal noise filter on the aligned, geometrically rectified images to generate a composite image of the LP for optical character recognition. In some examples, the camera device may include an image sensor, such as a high dynamic range (HDR) sensor, modified to set long and short exposures of the HDR sensor to capture frames of a vehicle's LP, but without consolidating the images into a composite image. The camera system may set optimal exposure settings based on detected relative speed of the vehicle.

A method and system for automated visual inspection, include receiving, from a camera imaging an inspection line, an image of the inspection line. The image includes an item on the inspection line personal or confidential image data. A processor produces from the image of the inspection line a reduced image, which does not include the personal or confidential image data, and inputs the reduced image to an inspection process.

The present application describes a system and method for extending a range of an image detection and classification system that is associated with various image capture devices. The range of the image detection and classification system is extended using one or more of an optical zoom on an area of interest, a digital zoom on the area of interest and a crop operation on the area of interest.

Various aspects of the system and methods described herein rely upon the operation of lateral flow assays specially configured to evaluate a bodily fluid for at least the presence or absence of pregnanediol glucuronide at a threshold selected from the range inclusive of 1 μg/mL-10 μg/mL. The results from the lateral flow assays are optionally interpreted in association with an application operating upon a mobile device or a system for the collection, interpretation and storage of results. The interpretations are useful in accordance with facilitating diagnoses and treatments associated with medical conditions related to the generated interpretations of the lateral flow assays.

Embodiments of this application provide an image processing method and apparatus, and a computer-readable storage medium. The image processing method includes obtaining an image and size information corresponding to the image; determining a target center point of the image according to position information of facial feature information in the image; determining cropped size information according to an aspect ratio relationship between the size information and target size information, the target size information being size information of a thumbnail that is to be generated and corresponds to the image; cropping the image based on the target center point and the cropped size information to obtain a target image, an aspect ratio of the target image being same as an aspect ratio of the target size information; and scaling the target image according to the target size information, to generate the thumbnail with the target size information.

A system and method relate to providing machine learning predictions with defenses against patch attacks. The system and method include obtaining a digital image and generating a set of location data via a random process. The set of location data include randomly selected locations on the digital image that provide feasible bases for creating regions for cropping. A set of random crops is generated based on the set of location data. Each crop includes a different region of the digital image as defined in relation to its corresponding location data. The machine learning system is configured to provide a prediction for each crop of the set of random crops and output a set of predictions. The set of predictions is evaluated collectively to determine a majority prediction from among the set of predictions. An output label is generated for the digital image based on the majority prediction. The output label includes the majority prediction as an identifier for the digital image.

An Artificial Intelligence (AI) roof deterioration analysis system that tracks changes in roofs over time by evaluating a series of features in high-resolution images.

Disclosed are techniques for processing image data. In some aspects, a three-dimensional model can be determined corresponding to an object in an input image. Based on the three-dimensional model, an estimated focal length can be determined that corresponds to the input image. An estimated depth associated with the object in the input image can be calculated based on the estimated focal length and an input image focal length.

Disclosed are various user-presence/absence detection techniques based on deep learning. These user-presence/absence detection techniques can include building/training a deep-learning model including a user-presence/absence classifier based on training images of a user-seating area of a surgeon console under various clinically-relevant conditions. The trained user-presence/absence classifier can then be used during teleoperation/surgical procedures to monitor/track users in the user-seating area of the surgeon console, and continuously classify captured real-time video images of the user-seating area into either a user-presence classification or a user-absence classification. In some embodiments, the disclosed techniques can be used to detect a user-switching event at the surgeon console when a second user is detected to have entered the user-seating area after a first user is detected to have exited the user-seating area. If the second user is identified as a new user, the disclosed techniques can trigger a recalibration procedure to recalibrate surgeon-console settings for the new user.