Abstract: Described herein are systems and methods that search videos and other media content to identify items, objects, faces, or other entities within the media content. Detectors identify objects within media content by, for instance, detecting a predetermined set of visual features corresponding to the objects. Detectors configured to identify an object can be trained using a machine learned model (e.g., a convolutional neural network) as applied to a set of example media content items that include the object. The systems provide user interfaces that allow users to review search results, pinpoint relevant portions of media content items where the identified objects are determined to be present, review detector performance and retrain detectors, providing search result feedback, and/or reviewing video monitoring results and analytics.

Abstract: Described herein are systems and methods that search videos and other media content to identify items, objects, faces, or other entities within the media content. Detectors identify objects within media content by, for instance, detecting a predetermined set of visual features corresponding to the objects. Detectors configured to identify an object can be trained using a machine learned model (e.g., a convolutional neural network) as applied to a set of example media content items that include the object. The systems and methods describe techniques that search videos and media content to determine the presence of unknown objects, generate novel detectors trained to identify the unknown objects, and apply the novel detectors to historical media content to identify previous appearances of the unknown objects.

Abstract: Described herein are systems and methods that search videos and other media content to identify items, objects, faces, or other entities within the media content. Detectors identify objects within media content by, for instance, detecting a predetermined set of visual features corresponding to the objects. Detectors configured to identify an object can be trained using a machine learned model (e.g., a convolutional neural network) as applied to a set of example media content items that include the object. The systems comprise an integrated detection unit configured to record media content, identify preferred content, and communicate the identifications of preferred content for storage in a computationally efficient manner.

Abstract: Described herein are systems and methods that search videos and other media content to identify items, objects, faces, or other entities within the media content. Detectors identify objects within media content by, for instance, detecting a predetermined set of visual features corresponding to the objects. Detectors configured to identify an object can be trained using a machine learned model (e.g., a convolutional neural network) as applied to a set of example media content items that include the object. The systems provide user interfaces that allow users to review search results, pinpoint relevant portions of media content items where the identified objects are determined to be present, review detector performance and retrain detectors, providing search result feedback, and/or reviewing video monitoring results and analytics.

Abstract: A charger for charging a pressure sensing catheter is provided. The charger can include a plurality of charging ports for receiving a portion of the proximal section of the pressure sensing catheter. The charging port may include an engagement portion for engaging with the portion of the proximal section of the pressure sensing catheter such that when the engagement portion engages with the proximal section of the pressure sensing catheter, the engagement portion is fluidly coupled to the catheter lumen and the pressure transmission medium from the engagement portion is displaced from the engagement portion to charge the one or more balloons of the pressure sensing catheter. The charger can include a cover for covering the engagement portion. The charger can include flutes defined on a surface of each charging port to permit a predetermined volume of the pressure transmission medium to be displaced from each charging port.

Abstract: Described herein are systems and methods that search videos and other media content to identify items, objects, faces, or other entities within the media content. Detectors identify objects within media content by, for instance, detecting a predetermined set of visual features corresponding to the objects. Detectors configured to identify an object can be trained using a machine learned model (e.g., a convolutional neural network) as applied to a set of example media content items that include the object. The systems provide user interfaces that allow users to review search results, pinpoint relevant portions of media content items where the identified objects are determined to be present, review detector performance and retrain detectors, providing search result feedback, and/or reviewing video monitoring results and analytics.

Abstract: Described herein are systems and methods that search videos and other media content to identify items, objects, faces, or other entities within the media content. Detectors identify objects within media content by, for instance, detecting a predetermined set of visual features corresponding to the objects. Detectors configured to identify an object can be trained using a machine learned model (e.g., a convolutional neural network) as applied to a set of example media content items that include the object. The systems provide user interfaces that allow users to review search results, pinpoint relevant portions of media content items where the identified objects are determined to be present, review detector performance and retrain detectors, providing search result feedback, and/or reviewing video monitoring results and analytics.

Abstract: Described herein are systems and methods that search videos and other media content to identify items, objects, faces, or other entities within the media content. Detectors identify objects within media content by, for instance, detecting a predetermined set of visual features corresponding to the objects. Detectors configured to identify an object can be trained using a machine learned model (e.g., a convolutional neural network) as applied to a set of example media content items that include the object. The systems provide user interfaces that allow users to review search results, pinpoint relevant portions of media content items where the identified objects are determined to be present, review detector performance and retrain detectors, providing search result feedback, and/or reviewing video monitoring results and analytics.

Abstract: Described herein are systems and methods that search videos and other media content to identify items, objects, faces, or other entities within the media content. Detectors identify objects within media content by, for instance, detecting a predetermined set of visual features corresponding to the objects. Detectors configured to identify an object can be trained using a machine learned model (e.g., a convolutional neural network) as applied to a set of example media content items that include the object. The systems provide user interfaces that allow users to review search results, pinpoint relevant portions of media content items where the identified objects are determined to be present, review detector performance and retrain detectors, providing search result feedback, and/or reviewing video monitoring results and analytics.

Abstract: Described herein are systems and methods that search videos and other media content to identify items, objects, faces, or other entities within the media content. Detectors identify objects within media content by, for instance, detecting a predetermined set of visual features corresponding to the objects. Detectors configured to identify an object can be trained using a machine learned model (e.g., a convolutional neural network) as applied to a set of example media content items that include the object. The systems provide user interfaces that allow users to review search results, pinpoint relevant portions of media content items where the identified objects are determined to be present, review detector performance and retrain detectors, providing search result feedback, and/or reviewing video monitoring results and analytics.

Abstract: A connector for connecting a pressure sensing catheter to charger is provided. The connector can include a first engagement portion engageable with a charger engagement portion of the charger to displace a pressure transmission medium in the charger engagement portion to charge one or more balloons of the pressure sensing catheter. The connector can have a handle that includes a tab terminating in an end surface engageable with an engagement surface of the charger when the first engagement portion engages with the charger engagement portion. The connector includes a distal abutment portion that engages with a portion of the charger engagement portion to provide an audible or tactile feedback, so as to prevent inadvertent overcharging of the balloons.

Abstract: A charger for charging a pressure sensing catheter is provided. The charger can include a plurality of charging ports for receiving a portion of the proximal section of the pressure sensing catheter. The charging port may include an engagement portion for engaging with the portion of the proximal section of the pressure sensing catheter such that when the engagement portion engages with the proximal section of the pressure sensing catheter, the engagement portion is fluidly coupled to the catheter lumen and the pressure transmission medium from the engagement portion is displaced from the engagement portion to charge the one or more balloons of the pressure sensing catheter. The charger can include a cover for covering the engagement portion. The charger can include flutes defined on a surface of each charging port to permit a predetermined volume of the pressure transmission medium to be displaced from each charging port.

Abstract: A connector for connecting a pressure sensing catheter to charger is provided. The connector can include a first engagement portion engageable with a charger engagement portion of the charger to displace a pressure transmission medium in the charger engagement portion to charge one or more balloons of the pressure sensing catheter. The connector can have a handle that includes a tab terminating in an end surface engageable with an engagement surface of the charger when the first engagement portion engages with the charger engagement portion. The connector includes a distal abutment portion that engages with a portion of the charger engagement portion to provide an audible or tactile feedback, so as to prevent inadvertent overcharging of the balloons.