Abstract:
A cloud computing system is disclosed. The cloud computing system includes a management server that manages a plurality of servers and distributes service resources. Each of the servers corresponds to one of a secure server type and a general server type, and the secure server type of server decrypts an encrypted code provided from a client. Accordingly, a secure server can execute a code requiring security. Especially, by classifying a program code as a general code or a secret code, the general server can also perform the partial function of a program.
Abstract:
A domain adaptation-based object recognition apparatus includes a memory configured to store a domain adaptation-based object recognition program and a processor configured to execute the program. The processor learns a generative model for generating a feature or an image similar to a gallery image on the basis of domain adaptation in association with an input probe image and learns an object recognition classification model by using a learning database corresponding to the gallery image and the input probe image, thereby performing object recognition using the input probe image.
Abstract:
Provided is an apparatus for online action detection, the apparatus including a feature extraction unit configured to extract a chunk-level feature of a video chunk sequence of a streaming video, a filtering unit configured to perform filtering on the chunk-level feature, and an action classification unit configured to classify an action class using the filtered chunk-level feature.
Abstract:
An image correcting method of the present invention includes: a step of performing a preprocessing process on an original image to generate a mask image including only an erased area of the original image; a step of predicting, by using generative adversarial networks, an image which is to be synthesized with the erased area in the mask image; and a step of synthesizing the predicted image with the erased area of the original image to generate a new image.
Abstract:
An electronic device according to an embodiment disclosed herein may include a memory including at least one instruction and a processor. By executing the at least one instruction, the processor may check feature information corresponding to a video and including at least one of an appearance-related feature value and a motion-related feature value from the video, calculate at least one of a starting score related to a starting point of an action instance, an ending score related to an ending point of an action instance, and a relatedness score between action instances on the basis of the feature information corresponding to the video, the action instances being included in the video, and generate an action proposal included in the video on the basis of the at least one score.
Abstract:
Provided is a dynamic object detecting technique, and more specifically, a system and method for determining a state of a motion of a camera on the basis of a local motion estimated on the basis of a video captured by a dynamic camera and a result of analyzing a global motion, flexibly updating a background model according to the state of the motion of the camera, and flexibly detecting a dynamic object according to the state of the motion of the camera.
Abstract:
Disclosed is an adaptive cache transformation architecture for a cache deployed forward to minimize duplicated transmission, by automatically storing content in a subscriber network area. The system for adaptively deploying a cache positioned at a subscriber network includes a cache service group configured to store all or a part of pieces of content serviced from one or more content providing apparatuses to one or more terminals and including a plurality of caches deployed at a subscriber network between the content providing apparatus and the terminal in a distributed manner, and a resource manager configured to transform a deployment structure of the plurality of caches forming the cache service group, based on at least one of an increase rate in the number of pieces of contents requested by the one or more terminals and a reutilization rate for each content.