Abstract: A pixel ray crossing-based multi-viewpoint MPI geometry generation method, device, and recording medium of the present disclosure, the method may comprise obtaining a multi-viewpoint image by original cameras which shoot a different viewpoint, obtaining a multi-plane image (MPI) based on the multi-viewpoint image, obtaining, based on the MPI, an atlas image in a 2D form, and obtaining a bitstream by encoding the atlas image.

Abstract: An embodiment armrest assembly for a vehicle includes an armrest rotatably coupled to an armrest board and configured to be extended from the armrest board by rotating forward or to be housed in the armrest board by rotating and standing and a speed-reduction damper mechanism connecting the armrest and the armrest board and configured to make a rotational speed of the armrest uniform by reducing the rotational speed when the armrest rotates to be extended.

Abstract: An embodiment armrest assembly for a vehicle includes an armrest including a main body and a lid, an armrest board to which the armrest is rotatably coupled and in which the armrest is accommodated in an erect state, and a skirt coupled to a rear bezel housing of the lid and to the armrest board and correspondingly covering a rear space of the lid when the armrest is rotated forward, wherein the skirt has a panel shape and includes a hard material.

Abstract: The present invention relates to a method and apparatus for filling a blank area of MPI view plane based on a pixel ray path. A method for generating multi plane image (MPI) data according to an embodiment of the present disclosure may comprise: calculating a pixel value according to each view for each photographed object, based on a plurality of input images photographed from a plurality of views; generating a view plane at a specific point by recording the calculated pixel value on one MPI layer determined based on the spatial position of the corresponding photographed object among a plurality of MPI layers; and generating MPI data by additionally recording the pixel value for the view.

Abstract: Disclosed is a storage method of sensed data used for state management of a logistics, which is performed by an apparatus including generating actual sensed data, which is obtained by sensing at least one of a temperature, acceleration, humidity, illuminance, inclination, impact, and location inside a region at a predetermined period through a first sensor installed inside the region where the logistics of a delivery vehicle is loaded, calculating a change amount of the actual sensed data at a predetermined time interval, activating one storage mode among a first storage mode and a second storage mode depending on a result of comparison between the change amount and a predetermined threshold change amount, and storing the actual sensed data in a storage method provided in the activated storage mode.

Abstract: Disclosed herein is a method for generating a texture map of a 3D mesh includes encoding a texture map of a 3D mesh, quantizing the encoded texture map, decoding the quantized texture map, performing rendering using the decoded texture map, and updating the texture map of the 3D mesh based on the value of a loss function.

Abstract: Disclosed herein are an apparatus and method for a multi-cloud service platform. The apparatus includes one or more processors and executable memory for storing at least one program executed by the one or more processors. The at least one program may receive a service request from a user client device, generate a multi-cloud infrastructure service using multiple clouds in response to the service request, make the multiple clouds interoperate with mufti-cloud infrastructure in order to provide the multi-cloud infrastructure service, and generate a multi-cloud application runtime environment corresponding to the multi-cloud infrastructure service.

Abstract: A method for manufacturing a semiconductor device and a semiconductor device produced thereby. For example and without limitation, various aspects of this disclosure provide a method for manufacturing a semiconductor device, and a semiconductor device produced thereby, that comprises an interposer without through silicon vias.

Abstract: Disclosed is a an apparatus for performing smart logistics monitoring including a display unit, a memory, a sensor unit sensing at least one of a temperature, acceleration, humidity, illuminance, inclination, impact, and location of an inside of a logistics vehicle, and a control unit that generates respective status information of a logistics according to a sensed result at a predetermined period, generates a respective QR code indicating the respective status information, and displays the respective QR code on a screen of the display unit. The respective QR code is converted and displayed on the screen depending on an order in which the respective QR code is generated.

Abstract: Disclosed is a display device including a display panel having a plurality of pixels, the display panel comprising a first display area having first resolution and a second display area having second resolution, the second resolution being lower than the first resolution, and a controller configured to generate display area information of each of the plurality of pixels, to blur an image that is displayed in the second display area based on the display area information, and to perform control such that the blurred image is displayed on the display panel.

Abstract: The present invention relates to a breast image analysis method with four mammogram images which are input to a convolutional neural network as one input and a system therefor and the system includes an image receiving unit which receives four mammogram images; an image size adjusting unit which adjusts a size of a mammogram image received from the image receiving unit; a preprocessing unit which performs preprocessing on the mammogram image adjusted by the image size adjusting unit; a convolutional neural network (CNN)-based CNN learning unit which generates learning information by learning the mammogram image preprocessed by the preprocessing unit; and a CNN inference unit which receives the learning information learned from the CNN learning unit and a mammogram image to be classified from the image receiving unit to diagnose a breast abnormality.

Abstract: A method for promoting growth and bioactive substances of Crepidiastrum denticulatum including performing a stress treatment on Crepidiastrum denticulatum during cultivation thereof, in which the stress treatment includes at least of applying visible light, drying, exposing to low temperature, irradiating ultraviolet rays, and applying a chemical elicitor.

Abstract: The present invention relates to a breast image analysis method with four mammogram images which are input to a convolutional neural network as one input and a system therefor and the system includes an image receiving unit which receives four mammogram images; an image size adjusting unit which adjusts a size of a mammogram image received from the image receiving unit; a preprocessing unit which performs preprocessing on the mammogram image adjusted by the image size adjusting unit; a convolutional neural network (CNN)-based CNN learning unit which generates learning information by learning the mammogram image preprocessed by the preprocessing unit; and a CNN inference unit which receives the learning information learned from the CNN learning unit and a mammogram image to be classified from the image receiving unit to diagnose a breast abnormality.

Abstract: Provided are a data processing apparatus and method for merging and processing deterministic knowledge and non-deterministic knowledge. The data processing apparatus and method may efficiently process various real-time and large-scale data to convert the data into knowledge by merging and processing non-deterministic knowledge and also deterministic knowledge perceived by an expert. Thus, it is possible to adaptively operate in accordance with a dynamically changing application service environment by converting a conversion rule for converting collected data generated from an application service system into semantic data, a context awareness rule for perceiving context information from given information, and a user query for searching for knowledge information into knowledge and gradually augmenting the knowledge information in accordance with an application service environment.

Abstract: An apparatus/method for extracting multiple features from time series data collected from a plurality of sensors and for performing transfer learning on them. There is provided an apparatus including: a multi-feature extraction unit for extracting multiple features from a data stream for each sensor inputted from the plurality of sensors; a transfer-learning model generation unit for extracting useful multi-feature information from a learning model which has finished pre-learning, for the multiple features for forwarding the extracted multi-feature information to a multi-feature learning unit to generate a learning model that performs transfer learning on the multiple features; and the multi-feature learning unit for receiving learning variables from the learning model for each of the multiple features and for performing parallel learning for the multiple features, to calculate and output a loss. In addition, there is provided an apparatus for detecting leaks in plant pipelines.

Abstract: Provided are an apparatus and method for detecting an anomaly in a plant pipe using multiple meta-learning. When a multi-sensor data stream about a plant pipe is received, each of a plurality of meta-learning modules for processing different packet section ranges, extracts one or more preset types of features from sensor data of packet section ranges set according to trend from an arbitrary reception time point, generates 2D image features of the features according to multi-sensor-specific times, generates 3D volume features by accumulating the 2D image features in a depth direction according to multiple sensors, and learns the 3D volume features in parallel through multi-sensor-specific learning modules. Results of the learning of the meta-learning modules are aggregated, and it is determined whether there is an anomaly in a plant pipe according to a learning result selected based on an optimal combination of multiple features, multiple sensors, and multiple packet sections.

Abstract: A method for promoting growth and bioactive substances of Crepidiastrum denticulatum including performing a stress treatment on Crepidiastrum denticulatum during cultivation thereof, in which the stress treatment includes at least of applying visible light, drying, exposing to low temperature, irradiating ultraviolet rays, and applying a chemical elicitor.

Abstract: Provided are an apparatus and method for detecting an anomaly in a plant pipe using multiple meta-learning. When a multi-sensor data stream about a plant pipe is received, each of a plurality of meta-learning modules for processing different packet section ranges, extracts one or more preset types of features from sensor data of packet section ranges set according to trend from an arbitrary reception time point, generates 2D image features of the features according to multi-sensor-specific times, generates 3D volume features by accumulating the 2D image features in a depth direction according to multiple sensors, and learns the 3D volume features in parallel through multi-sensor-specific learning modules. Results of the learning of the meta-learning modules are aggregated, and it is determined whether there is an anomaly in a plant pipe according to a learning result selected based on an optimal combination of multiple features, multiple sensors, and multiple packet sections.

Abstract: Provided is a data meta-scaling method. The data meta-scaling method optimizes an abbreviation criterion for abbreviating data through continuous knowledge augmentation in various dimensions which enable expression of data in a process of performing machine learning.