Abstract: Systems and methods are provided for identifying customers aboard a cruise ship for provision of products and location access and for embarkation or disembarkation. Systems can include a data store on the cruise ship storing customer profiles of customers, a plurality of networked computing devices including image capture devices, and a processor in communication with the data store and the networked computing devices. The processor receives access requests in conjunction with images of the requestors, uses facial recognition software algorithms to identify the requestor as a customer entitled to the requested access, based on facial recognition data stored for the customer, and causes access to be granted to the customer. Confidence levels of facial recognition results may be improved by combining initial facial recognition results with additional cruise-specific information associated with customers.

Abstract: Summarizing, the application relates to a machine-learning system for adaptively changing a matching threshold of a biometric system. The machine-learning system comprises a batch aggregator device operable to receive input data from the biometric system via a communication interface and to aggregate a batch of at least some of the received input data. The machine-learning system further comprises a learning expert device operable to compute a new suggestion for a matching threshold value of the biometric system based on the aggregated batch. Finally, the machine-learning system comprises an output device operable to output the computed new suggestion for the matching threshold of the biometric system via the communication interface.

Abstract: Summarizing, the application relates to a machine-learning system for adaptively changing a matching threshold of a biometric system. The machine-learning system comprises a batch aggregator device operable to receive input data from the biometric system via a communication interface and to aggregate a batch of at least some of the received input data. The machine-learning system further comprises a learning expert device operable to compute a new suggestion for a matching threshold value of the biometric system based on the aggregated batch. Finally, the machine-learning system comprises an output device operable to output the computed new suggestion for the matching threshold of the biometric system via the communication interface.

Abstract: A device may receive identity information associated with an identity, and may determine a relationship between at least one of: the identity and another identity, or the identity and an attribute. The device may determine a credibility score, associated with the relationship, that indicates a likelihood that the relationship is an accurate representation of the identity. The device may determine a confidence score based on the identity information and the credibility score, and may output or store the confidence score.