Abstract: Disclosed are systems and methods for dynamically determining categories for images. A computer-implemented method includes training a neural network to receive an input image and determine one or more image categories associated with the input image; obtaining a set of images associated with a user; and determining, using the trained neural network, one or more image categories associated with each image included in the obtained set of images.

Abstract: Techniques for text evaluation are provided. A curated dataset comprising a plurality of textual documents is received. A tree of classifiers is trained, based on the curated dataset, to identify use cases. A feature graph model is generated, based on the curated dataset, to determine textual similarity. A new document is received, and a plurality of requirements is extracted from the new document. For each requirement, one or more vector scores are generated by evaluating the requirement using the tree of classifiers, one or more feature scores are generated by evaluating the requirement using the feature graph model, and one or more use cases are identified for the new textual document based on the one or more vector scores and the one or more feature scores. An implementation is generated for the new document based on the one or more use cases.

Abstract: A network element includes a plurality of ports interconnected by a switching fabric, wherein a port includes a plurality of connections including an infrastructure connection that operates a Bidirectional Forwarding Detection (BFD) session and a group of connections that share a similar fate for a fault as the infrastructure connection; and a controller configured to detect a fault on the infrastructure connection via the BFD session, and cause a protection switch for one or more of the group of connections based on the fault on the infrastructure connection. The infrastructure connection and the group of connections can be Pseudowires (PWE) or Label Switched Paths (LSPs) in a Multiprotocol Label Switching (MPLS) network.

Abstract: Systems and methods for information retrieval are described. Embodiments generate a dense embedding for each of a plurality of media objects to be searched, generate a sparse embedding for each of the media objects using an encoder that takes the dense embedding as an input, wherein the sparse embedding satisfies a sparsity constraint that is applied to at least one layer of the encoder during training, and perform a search on the plurality of media objects based at least in part on the sparse embedding.

Abstract: A node includes one or more line cards interconnected to one another via a switching fabric and configured to implement a data plane; and a first router processor and a second router processor communicatively coupled to the one or more line cards, and each configured to implement a separate control plane, such that the node appears in a link-state database as two separate nodes. Responsive to an in-service software upgrade, the first router processor is upgraded and down while the second router processor is active, thereby preserving routing and forwarding. The one or more line cards include a first Virtual Local Area Networking (VLAN) for the first router processor and a second VLAN for the second router processor, and the first VLAN and the second VLAN are associated with a same physical interface on the one or more line cards.

Abstract: Systems and methods include receiving one or more Ethernet Virtual Private Network (EVPN) advertisements from one or more peer nodes with information including any of traffic characterization information and traffic control information; and providing traffic to the EVPN and to the corresponding one or more peer nodes based on the information from the corresponding one or more peer nodes. The one or more EVPN advertisements can be in an EVPN Network Layer Reachability Information (NLRI) advertisement, and the EVPN NLRI can have Route Type 1 for the information to apply to an EVPN Instance (EVI) and the EVPN NLRI can have Route Type 2 for the information to apply to a specific customer node based on a Media Access Control (MAC).

Abstract: Disclosed are systems and methods for dynamically determining categories for images. A computer-implemented method includes training a neural network to receive an input image and determine one or more image categories associated with the input image; obtaining a set of images associated with a user; and determining, using the trained neural network, one or more image categories associated with each image included in the obtained set of images.

Abstract: Systems and methods include receiving one or more Ethernet Virtual Private Network (EVPN) advertisements from one or more peer nodes with information including any of traffic characterization information and traffic control information; and providing traffic to the EVPN and to the corresponding one or more peer nodes based on the information from the corresponding one or more peer nodes. The one or more EVPN advertisements can be in an EVPN Network Layer Reachability Information (NLRI) advertisement, and the EVPN NLRI can have Route Type 1 for the information to apply to an EVPN Instance (EVI) and the EVPN NLRI can have Route Type 2 for the information to apply to a specific customer node based on a Media Access Control (MAC).

Abstract: Techniques are disclosed for parsing a source image, to identify segments of one or more objects within the source image. The parsing is carried out by an image parsing pipeline that includes three distinct stages comprising three respectively neural network models. The source image can include one or more objects. A first neural network model of the pipeline identifies a section of the source image that includes the object comprising a plurality of segments. A second neural network model of the pipeline generates, from the section of the source image, a mask image, where the mask image identifies one or more segments of the object. A third neural network model of the pipeline further refines the identification of the segments in the mask image, to generate a parsed image. The parsed image identifies the segments of the object, by assigning corresponding unique labels to pixels of different segments of the object.

Abstract: A node includes one or more line cards interconnected to one another via a switching fabric and configured to implement a data plane; and a first router processor and a second router processor communicatively coupled to the one or more line cards, and each configured to implement a separate control plane, such that the node appears in a link-state database as two separate nodes. Responsive to an in-service software upgrade, the first router processor is upgraded and down while the second router processor is active, thereby preserving routing and forwarding. The one or more line cards include a first Virtual Local Area Networking (VLAN) for the first router processor and a second VLAN for the second router processor, and the first VLAN and the second VLAN are associated with a same physical interface on the one or more line cards.

Abstract: A Point of Local Repair (PLR) network element includes one or more ports and circuitry connected thereto for forwarding and control, wherein the circuitry is configured to receive a PATH message for a Label Switched Path (LSP) tunnel in a Multiprotocol Label Switching (MPLS) network with a specified DiffSery Traffic Engineering (DSTE) Class Type, determine the DSTE Class Type based on the PATH message, and store the DSTE Class Type for the LSP tunnel to ensure a Facility Bypass tunnel used for the LSP tunnel supports the specified DSTE Class Type. The circuitry can be further configured to, responsive to a failure of the LSP tunnel, select the Facility Bypass tunnel for the LSP tunnel such that the Facility Bypass tunnel supports the specified DSTE Class Type.

Abstract: Techniques for text evaluation are provided. A curated dataset comprising a plurality of textual documents is received. A tree of classifiers is trained, based on the curated dataset, to identify use cases. A feature graph model is generated, based on the curated dataset, to determine textual similarity. A new document is received, and a plurality of requirements is extracted from the new document. For each requirement, one or more vector scores are generated by evaluating the requirement using the tree of classifiers, one or more feature scores are generated by evaluating the requirement using the feature graph model, and one or more use cases are identified for the new textual document based on the one or more vector scores and the one or more feature scores. An implementation is generated for the new document based on the one or more use cases.

Abstract: The present disclosure relates to an image merging system that automatically and seamlessly detects and merges missing people for a set of digital images into a composite group photo. For instance, the image merging system utilizes a number of models and operations to automatically analyze multiple digital images to identify a missing person from a base image, segment the missing person from the second image, and generate a composite group photo by merging the segmented image of the missing person into the base image. In this manner, the image merging system automatically creates merged group photos that appear natural and realistic.

Abstract: A process for regenerating a temperature swing adsorption unit comprising: sending a heated purge gas stream through an adsorption bed to remove impurities from said adsorption bed and producing a contaminated stream; sending said contaminated stream to a separator to produce a liquid stream and a vapor stream; returning said vapor stream as at least a portion of said heated purge stream until said vapor stream comprises above a predetermined level of impurities; and purging a portion of said vapor stream until the heated purge stream has a level of impurities below a second predetermined level.

Abstract: Techniques are disclosed for parsing a source image, to identify segments of one or more objects within the source image. The parsing is carried out by an image parsing pipeline that includes three distinct stages comprising three respectively neural network models. The source image can include one or more objects. A first neural network model of the pipeline identifies a section of the source image that includes the object comprising a plurality of segments. A second neural network model of the pipeline generates, from the section of the source image, a mask image, where the mask image identifys one or more segments of the object. A third neural network model of the pipeline further refines the identification of the segments in the mask image, to generate a parsed image. The parsed image identifies the segments of the object, by assigning corresponding unique labels to pixels of different segments of the object.

Abstract: Systems and methods, in a Label Edge Router (LER) which includes one or more ports and a switching fabric therebetween, include, responsive to a request for a Label Switched Path (LSP) tunnel with a specified DiffServ Traffic Engineering (DSTE) Class Type, signaling a PATH message via a port for the LSP tunnel in a Multiprotocol Label Switching (MPLS) network; incorporating a FAST_REROUTE object in the PATH message which indicates Facility Bypass is desired; and incorporating the DSTE Class Type in the FAST_REROUTE object of the PATH message for a Point of Local Repair (PLR) node in the MPLS network to ensure a Facility Bypass tunnel used for the LSP tunnel supports the specified DSTE Class Type.

Abstract: Systems and methods for controlling cache usage are described and include associating, by a server computing system, a tenant in a multi-tenant environment with a cache cluster formed by a group of cache instances; associating, by the server computing system, a memory threshold and a burst memory threshold with the tenant; enabling, by the server computing system, each of the cache instances to collect metrics information based on the tenant accessing the cache cluster, the metrics information used to determine memory usage information and burst memory usage information of the cache cluster by the tenant; and controlling, by the server computing system, usage of the cache cluster by the tenant based on comparing the memory usage information with the memory threshold and comparing the burst memory usage information with the burst memory threshold.

Abstract: A node includes a plurality of ports configured to provide a service over a primary Multi-Segment Pseudowire (MS-PW) and a backup MS-PW in a network; a switching fabric interconnecting the plurality of ports; and a controller communicatively coupled to the plurality of ports and the switching fabric, wherein the controller is configured to receive a pseudowire status message for each of the primary MS-PW and the backup MS-PW, determine a Signal Degrade condition on one of the primary MS-PW and the backup MS-PW based on the pseudowire status message, and cause a switch of the service to an inactive one of the primary MS-PW and the backup MS-PW based on a Signal Degrade condition on an active one of the primary MS-PW and the backup MS-PW. The controller can further provide a trap to a management system based on the determined Signal Degrade condition.

Abstract: There is described a computing device and method in a digital medium environment for custom auto tagging of multiple objects. The computing device includes an object detection network and multiple image classification networks. An image is received at the object detection network and includes multiple visual objects. First feature maps are applied to the image at the object detection network and generate object regions associated with the visual objects. The object regions are assigned to the multiple image classification networks, and each image classification network is assigned to a particular object region. The second feature maps are applied to each object region at each image classification network, and each image classification network outputs one or more classes associated with a visual object corresponding to each object region.

Abstract: Disclosed are some implementations of systems, apparatus, methods and computer program products for deploying software applications on server clusters. Characteristics of the server clusters are used to generate a deployment plan indicating an order in which the server clusters are to be updated and a timing with which the server clusters are to be updated. The characteristics of a server cluster can include a risk rating associated with the server cluster, an amount of traffic processed by the server cluster, and/or a size of the server cluster.