Abstract: In a case of receiving an access request to a target image, an image access management device can provide an appropriate access right holder with an appropriate range of information by determining a browsing level with respect to the target image according to an access authority or purpose included in the access request to the target image, by an access management unit, by generating a final image that corresponds to the access authority by processing the feature vector according to the browsing level, and providing the generated final image as a response to the access request, by an image generation unit.

Abstract: In a data driven object recognition system and object recognition method, a connection relationship between an object feature extraction unit and a plurality of task-specific identification units is stored in a connection switch according to a type of task. The connection relationship is changed based on the connection information to suppress the amount of labeling in constructing a learning data set.

Abstract: Aspects of the disclosure relate to a method for discovering latent factors from data in a neural network environment. Aspects include adding, by a data noise unit of the neural network environment, noise to a set of input data; computing, by the encoder model and a set of stochastic non-linear units, a set of latent code based on the set of input data; obtaining, by decoding the latent code with a decoder model, a set of reconstructed data.

Abstract: An object of the disclosure is to provide flexible and highly accurate activity detection means. Provided is an activity detection device including: an input unit that inputs an image sequence including a first image and a second image; an object detection unit that detects a first object in the image sequence; a component model unit that generates first characteristic information characterizing the first object and includes at least one individually trainable component model; and an activity detection unit that generates a first object state corresponding to the first object in the first image and a second object state corresponding to the first object in the second image based on the first characteristic information and determines an activity related to the first object based on the first and second object states.

Abstract: In a case of receiving an access request to a target image, an image access management device can provide an appropriate access right holder with an appropriate range of information by determining a browsing level with respect to the target image according to an access authority or purpose included in the access request to the target image, by an access management unit, by generating a final image that corresponds to the access authority by processing the feature vector according to the browsing level, and providing the generated final image as a response to the access request, by an image generation unit.

Abstract: A connection relationship between an object feature extraction unit and a plurality of task-specific identification units is changed based on connection information stored in a connection switch according to a type of a task.

Abstract: Aspects of the disclosure relate to a method for discovering latent factors from data in a neural network environment. Aspects include adding, by a data noise unit of the neural network environment, noise to a set of input data; computing, by the encoder model and a set of stochastic non-linear units, a set of latent code based on the set of input data; obtaining, by decoding the latent code with a decoder model, a set of reconstructed data.

Abstract: An object detection method that is provided with a step for extracting a plurality of reference feature vectors related to a local area from an image representing an object, and extracting a plurality of query feature vectors related to the local area from a search query image; a step for matching each query feature vector against each reference feature vector, and calculating a similarity score having a value that is higher the closer the distance between both vectors, the larger the local area for which the query feature vector has been extracted, and the larger the local area for which a matching reference feature vector has been extracted; a step for determining a reference feature vector for which a similarity score is highest as the similar vector for each query feature vector; and a step for acquiring a final score by object associated with the similar vectors, and setting the object returning the highest score as the detection result; and wherein the score is calculated by dividing a sum of the simila

Abstract: An object detection method that is provided with a step for extracting a plurality of reference feature vectors related to a local area from an image representing an object, and extracting a plurality of query feature vectors related to the local area from a search query image; a step for matching each query feature vector against each reference feature vector, and calculating a similarity score having a value that is higher the closer the distance between both vectors, the larger the local area for which the query feature vector has been extracted, and the larger the local area for which a matching reference feature vector has been extracted; a step for determining a reference feature vector for which a similarity score is highest as the similar vector for each query feature vector; and a step for acquiring a final score by object associated with the similar vectors, and setting the object returning the highest score as the detection result; and wherein the score is calculated by dividing a sum of the simila