System and method for context aware access control with weapons detection

    公开(公告)号:US11482088B1

    公开(公告)日:2022-10-25

    申请号:US17304506

    申请日:2021-06-22

    Abstract: Techniques for context aware access control with weapons detection are provided. An indication of an identity of a person is received at an access control system. The indication of the identity of the person includes a confidence level of the identification. An indication of a threat level of the person is received at a threat detection system. The threat level including a confidence level of the threat level. At least one of an identification threshold or a threat level threshold is modified based on the threat level confidence level or the confidence level of the identification. At least one of allowing access, allowing access with an alarm indication, or denying access to the person is based in part on the modified identification threshold or threat level threshold.

    Method and system for facilitating improved training of a supervised machine learning process

    公开(公告)号:US10997469B2

    公开(公告)日:2021-05-04

    申请号:US16581110

    申请日:2019-09-24

    Abstract: Methods, systems, and techniques for facilitating improved training of a supervised machine learning process, such as a decision tree. First and second object detections of an object depicted in a video are respectively generated using first and second object detectors, with the second object detector requiring more computational resources than the first object detector to detect the object. Whether a similarity and a difference between the first and second object detections respectively satisfy a similarity threshold and a difference threshold is determined. When the similarity threshold is satisfied, the first object detection is stored as a positive example for the machine learning training. When the difference threshold is satisfied, the first object detection is stored as a negative example for the machine learning training.

    Face and inner canthi detection for thermographic body temperature measurement

    公开(公告)号:US11326956B2

    公开(公告)日:2022-05-10

    申请号:US16987099

    申请日:2020-08-06

    Abstract: One example temperature sensing device includes an electronic processor configured to receive a thermal image of a person captured by a thermal camera. The electronic processor is configured to determine a first temperature and a first location of a first hotspot on the person. The electronic processor is configured to determine a second location of a second hotspot on the person based on the second location being approximately symmetrical with respect to the first location about an axis, and the second hotspot having a second temperature that is approximately equal to the first temperature. The electronic processor is configured to determine a distance between the first location of the first hotspot and the second location of the second hotspot. In response to determining that the distance is within the predetermined range of distances, the electronic processor is configured to generate and output an estimated temperature of the person.

    METHOD AND SYSTEM FOR FACILITATING IMPROVED TRAINING OF A SUPERVISED MACHINE LEARNING PROCESS

    公开(公告)号:US20210089833A1

    公开(公告)日:2021-03-25

    申请号:US16581110

    申请日:2019-09-24

    Abstract: Methods, systems, and techniques for facilitating improved training of a supervised machine learning process, such as a decision tree. First and second object detections of an object depicted in a video are respectively generated using first and second object detectors, with the second object detector requiring more computational resources than the first object detector to detect the object. Whether a similarity and a difference between the first and second object detections respectively satisfy a similarity threshold and a difference threshold is determined. When the similarity threshold is satisfied, the first object detection is stored as a positive example for the machine learning training. When the difference threshold is satisfied, the first object detection is stored as a negative example for the machine learning training.

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