Abstract: A method includes: receiving, at a cluster controller of a first cluster, a request for pairing a first datastore of the first cluster to a second datastore of a second cluster, wherein each of the first cluster and the second cluster includes a plurality of datastores; determining whether the first datastore is available for pairing; in response to determining that the first datastore is available for pairing, generating an entry in a mapping table indicating that the first datastore is paired with the second datastore; receiving information associated with the second datastore; and in response to receiving the information, storing the information in the first datastore. The second cluster performs similar operations as those performed by the first cluster to achieve a bidirectional reservation between the first cluster and the second cluster.

Abstract: A system for remote identification of users. The system uses deep learning techniques for authenticating a user from an identification document and using automated verification of identification documents. Identification documents may be authenticated by validating security features. The system may determine features expected in a valid identification document and determine whether those features are present, employing techniques, such as determining whether direction-sensitive features are present. Liveness of a user indicated by the identification document may be determined with a deep learning model trained for identification of facial spoofing attacks.

Abstract: A method includes: receiving, at a cluster controller of a first cluster, a request for pairing a first datastore of the first cluster to a second datastore of a second cluster, wherein each of the first cluster and the second cluster includes a plurality of datastores; determining whether the first datastore is available for pairing; in response to determining that the first datastore is available for pairing, generating an entry in a mapping table indicating that the first datastore is paired with the second datastore; receiving information associated with the second datastore; and in response to receiving the information, storing the information in the first datastore. The second cluster performs similar operations as those performed by the first cluster to achieve a bidirectional reservation between the first cluster and the second cluster.

Abstract: A method includes: receiving, at a cluster controller of a first cluster, a request for pairing a first datastore of the first cluster to a second datastore of a second cluster, wherein each of the first cluster and the second cluster includes a plurality of datastores; determining whether the first datastore is available for pairing; in response to determining that the first datastore is available for pairing, generating an entry in a mapping table indicating that the first datastore is paired with the second datastore; receiving information associated with the second datastore; and in response to receiving the information, storing the information in the first datastore. The second cluster performs similar operations as those performed by the first cluster to achieve a bidirectional reservation between the first cluster and the second cluster.

Abstract: A system for remote identification of users. The system uses deep learning techniques for authenticating a user from an identification document, using automated verification of identification documents and detection that a live person identified by the document is present. Liveness of a user indicated by the identification document may be determined with a deep learning model trained for identification of facial spoofing attacks. The deep learning model may be trained using training data extracted from facial feature locations of training images.

Abstract: A method includes: receiving, at a cluster controller of a first cluster, a request for pairing a first datastore of the first cluster to a second datastore of a second cluster, wherein each of the first cluster and the second cluster includes a plurality of datastores; determining whether the first datastore is available for pairing; in response to determining that the first datastore is available for pairing, generating an entry in a mapping table indicating that the first datastore is paired with the second datastore; receiving information associated with the second datastore; and in response to receiving the information, storing the information in the first datastore. The second cluster performs similar operations as those performed by the first cluster to achieve a bidirectional reservation between the first cluster and the second cluster.

Abstract: A method includes: receiving, at a cluster controller of a first cluster, a request for pairing a first datastore of the first cluster to a second datastore of a second cluster, wherein each of the first cluster and the second cluster includes a plurality of datastores; determining whether the first datastore is available for pairing; in response to determining that the first datastore is available for pairing, generating an entry in a mapping table indicating that the first datastore is paired with the second datastore; receiving information associated with the second datastore; and in response to receiving the information, storing the information in the first datastore. The second cluster performs similar operations as those performed by the first cluster to achieve a bidirectional reservation between the first cluster and the second cluster.

Abstract: A system for remote identification of users. The system uses deep learning techniques for authenticating a user from an identification document and using automated verification of identification documents. Identification documents may be authenticated by validating security features. The system may determine features expected in a valid identification document and determine whether those features are present, employing techniques, such as determining whether direction-sensitive features are present. Liveness of a user indicated by the identification document may be determined with a deep learning model trained for identification of facial spoofing attacks.

Abstract: A system for remote identification of users. The system uses deep learning techniques for authenticating a user from an identification document, using automated verification of identification documents and detection that a live person identified by the document is present. Liveness of a user indicated by the identification document may be determined with a deep learning model trained for identification of facial spoofing attacks. The deep learning model may be trained using training data extracted from facial feature locations of training images.