Abstract:
A method and an apparatus for compressing a content name are provided. In the method, a controller constructs a content name tree according to content names in a content database, where a first node of the content name tree stores a first-level prefix of a content name in the content database, and an Nth-level node of the content name tree stores prefixes of first N levels of the content name; and then the controller compresses a content name stored in the Mth-level node into a first content name stored in a father node of the Mth-level node when determining that the content name stored in each Mth-level node in the content name tree is corresponding to a first network node in a network. Thus, compression of a content name in a content name database is achieved, and space occupied by the content name is saved.
Abstract:
An image processing method, a related device, and a computer storage medium are provided. The method includes: obtaining a feature intensity image corresponding to a training image, where an intensity value of a pixel in the feature intensity image is used to indicate importance of the pixel for recognizing the training image, and resolution of the training image is the same as resolution of the feature intensity image; and occluding, based on the feature intensity image, a to-be-occluded region in the training image by using a preset window, to obtain a new image, where the to-be-occluded region includes a to-be-occluded pixel, and the new image is used to update an image recognition model. According to the embodiments of the present application, a prior-art problem that a model has low accuracy and relatively poor generalization performance because of limited training data can be resolved.
Abstract:
A method and an apparatus for recognizing a descriptive attribute of an appearance feature include obtaining a location feature of an appearance feature of a target image to determine a location of a part of an object in a preset object model indicated by the appearance feature, where the location feature of the appearance feature indicates the location of the part of the object in the preset object model indicated by the appearance feature, recognizing a target region based on the location feature, where the target region includes the part of the object, performing feature analysis on the target region, recognizing a descriptive attribute of the appearance feature of the object, and determining the location feature of the appearance feature having a local attribute.
Abstract:
A method and an apparatus for compressing a content name are provided. In the method, a controller constructs a content name tree according to content names in a content database, where a first node of the content name tree stores a first-level prefix of a content name in the content database, and an Nth-level node of the content name tree stores prefixes of first N levels of the content name; and then the controller compresses a content name stored in the Mth-level node into a first content name stored in a father node of the Mth-level node when determining that the content name stored in each Mth-level node in the content name tree is corresponding to a first network node in a network. Thus, compression of a content name in a content name database is achieved, and space occupied by the content name is saved.
Abstract:
An image super-resolution method includes preprocessing the low-resolution image to obtain a vertical gradient map, a horizontal gradient map, and a luminance map, which are used as three different dimensions of information to constitute a to-be-input feature map, performing size conversion on the to-be-input feature map to obtain an input feature map, performing nonlinear transformation on the input feature map to obtain an input feature map obtained after the nonlinear transformation, and performing weighted processing on the input feature map and the input feature map obtained after the nonlinear transformation, to obtain an output feature map, performing size conversion on the output feature map to obtain a residual map, and combining the low-resolution image and the residual map to obtain a high-resolution image.
Abstract:
An image super-resolution method includes preprocessing the low-resolution image to obtain a vertical gradient map, a horizontal gradient map, and a luminance map, which are used as three different dimensions of information to constitute a to-be-input feature map, performing size conversion on the to-be-input feature map to obtain an input feature map, performing nonlinear transformation on the input feature map to obtain an input feature map obtained after the nonlinear transformation, and performing weighted processing on the input feature map and the input feature map obtained after the nonlinear transformation, to obtain an output feature map, performing size conversion on the output feature map to obtain a residual map, and combining the low-resolution image and the residual map to obtain a high-resolution image.
Abstract:
Methods and apparatuses for routing and forwarding, establishing a routing table, and acquiring content are provided. The method for routing and forwarding includes: receiving a content request packet, where the content request packet carries a content name of requested content and container information of the requested content; determining whether any forwarding entry that matches the content name of the requested content exists in a FIB; determining whether any forwarding entry that matches the container identifier in the container information exists in the FIB when no forwarding entry that matches the content name of the requested content exists in the FIB; and when a forwarding entry that matches the container identifier in the container information of the requested content exists in the FIB, sending the content request packet according to a port in the matched forwarding entry.
Abstract:
A method, an apparatus, and a system for transmitting data are disclosed. In an embodiment, the includes receiving a detection interest packet, generating a detection response data packet according to a content name, and adding a mobility status of a first network node to a status record entry, sending the detection response data packet to a second network node so that the second network node adds a mobility status of the second network node to a first status record entry and sends the detection response data packet to a client. The client determines a revised value of a first expected distance according to the first status record entry and the first expected distance, generates a request interest packet, sends the request interest packet to at least one network node and receives the request interest packet sent by the second network node.
Abstract:
Methods and apparatuses for routing and forwarding, establishing a routing table, and acquiring content are provided. The method for routing and forwarding includes: receiving a content request packet, where the content request packet carries a content name of requested content and container information of the requested content; determining whether any forwarding entry that matches the content name of the requested content exists in a FIB; determining whether any forwarding entry that matches the container identifier in the container information exists in the FIB when no forwarding entry that matches the content name of the requested content exists in the FIB; and when a forwarding entry that matches the container identifier in the container information of the requested content exists in the FIB, sending the content request packet according to a port in the matched forwarding entry.
Abstract:
A method, an apparatus, and a system for transmitting data are disclosed. In an embodiment, the includes receiving a detection interest packet, generating a detection response data packet according to a content name, and adding a mobility status of a first network node to a status record entry, sending the detection response data packet to a second network node so that the second network node adds a mobility status of the second network node to a first status record entry and sends the detection response data packet to a client. The client determines a revised value of a first expected distance according to the first status record entry and the first expected distance, generates a request interest packet, sends the request interest packet to at least one network node and receives the request interest packet sent by the second network node.