Abstract: A display device, includes: a display area and a non-display area; a plurality of signal lines over the display area; and a plurality of connection lines in the display area and connected to the signal lines, wherein the plurality of connection lines includes a plurality of first connection lines connected to the signal lines, respectively, a plurality of third connection lines on a same layer as the first connection lines, and a plurality of second connection lines connecting the first connection lines to the third connection lines.

Abstract: Provided is a method for electrowinning neodymium compound. The method includes providing a fluoride-based electrolyte through an opening defined in an electrolytic bath including a cathode and an anode. The method includes providing granules, each including a neodymium compound and having at least one cavity defined therein, through the opening defined in the electrolytic bath. The method includes dissolving at least a portion of the granule in a molten salt of the fluoride-based electrolyte. The method also includes reducing neodymium at the cathode. The cavity is defined inside or on the surface of the granule, and the apparent density of the granules is lower than the density of the molten salt. The method proposed has an improved process compared to those of the related art.

Abstract: A processor-implemented method includes generating a preprocessed infrared (IR) image by performing first preprocessing based on an IR image including an object; generating a preprocessed depth image by performing second preprocessing based on a depth image including the object; and determining whether the object is a genuine object based on the preprocessed IR image and the preprocessed depth image

Abstract: A processor-implemented method includes: generating a preprocessed infrared (IR) image by performing first preprocessing based on an IR image including an object; generating a preprocessed depth image by performing second preprocessing based on a depth image including the object; and determining whether the object is a genuine object based on the preprocessed IR image and the preprocessed depth image.

Abstract: A user authentication method and a user authentication apparatus acquire an input image including a frontalized face of a user, calculate a confidence map including confidence values, for authenticating the user, corresponding to pixels with values maintained in a depth image of the frontalized face of the user among pixels included in the input image, extract a second feature vector from a second image generated based on the input image and the confidence map, acquire a first feature vector corresponding to an enrolled image, and perform authentication of the user based on a correlation between the first feature vector and the second feature vector.

Abstract: A user authentication method and a user authentication apparatus acquire an input image including a frontalized face of a user, calculate a confidence map including confidence values, for authenticating the user, corresponding to pixels with values maintained in a depth image of the frontalized face of the user among pixels included in the input image, extract a second feature vector from a second image generated based on the input image and the confidence map, acquire a first feature vector corresponding to an enrolled image, and perform authentication of the user based on a correlation between the first feature vector and the second feature vector.

Abstract: A processor-implemented method with object tracking includes: determining an initial template image based on an input bounding box and an input image; generating an initial feature map by extracting features from the initial template image; generating a transformed feature map by performing feature transformation adapted to objectness on the initial feature map; generating an objectness probability map and a bounding box map indicating bounding box information corresponding to each coordinate of the objectness probability map by performing objectness-based bounding box regression analysis on the transformed feature map; and determining a refined bounding box based on the objectness probability map and the bounding box map.

Abstract: A processor-implemented object tracking method includes: setting a suppressed region in a template image based on a shape of a target box of the template image; refining a template feature map of the template image by suppressing an influence of feature data corresponding to the suppressed region in the template feature map; and tracking an object by determining a bounding box corresponding to the target box in a search image based on the refined template feature map.

Abstract: A user authentication method and a user authentication apparatus acquire an input image including a frontalized face of a user, calculate a confidence map including confidence values, for authenticating the user, corresponding to pixels with values maintained in a depth image of the frontalized face of the user among pixels included in the input image, extract a second feature vector from a second image generated based on the input image and the confidence map, acquire a first feature vector corresponding to an enrolled image, and perform authentication of the user based on a correlation between the first feature vector and the second feature vector.

Abstract: A processor-implemented method with object tracking includes: determining an initial template image based on an input bounding box and an input image; generating an initial feature map by extracting features from the initial template image; generating a transformed feature map by performing feature transformation adapted to objectness on the initial feature map; generating an objectness probability map and a bounding box map indicating bounding box information corresponding to each coordinate of the objectness probability map by performing objectness-based bounding box regression analysis on the transformed feature map; and determining a refined bounding box based on the objectness probability map and the bounding box map.

Abstract: A user authentication method and a user authentication apparatus acquire an input image including a frontalized face of a user, calculate a confidence map including confidence values, for authenticating the user, corresponding to pixels with values maintained in a depth image of the frontalized face of the user among pixels included in the input image, extract a second feature vector from a second image generated based on the input image and the confidence map, acquire a first feature vector corresponding to an enrolled image, and perform authentication of the user based on a correlation between the first feature vector and the second feature vector.

Abstract: A processor-implemented object tracking method includes: setting a suppressed region in a template image based on a shape of a target box of the template image; refining a template feature map of the template image by suppressing an influence of feature data corresponding to the suppressed region in the template feature map; and tracking an object by determining a bounding box corresponding to the target box in a search image based on the refined template feature map.

Abstract: The present invention relates to a use of agar-derived oligosaccharides for inhibiting the growth of Staphylococcus. More specifically, the present invention provides, as a material for medicine, food, cosmetics and the like, a use of agar-derived agarooligosaccharides, agarobiose or AHG, which have an effect of inhibiting the growth of Staphylococcus or killing the same.

Abstract: A processor-implemented neural network method includes: determining, using a neural network, a feature vector based on a training image of a first class among a plurality of classes; determining, using the neural network, plural feature angles between the feature vector and class vectors of other classes among the plurality of classes; determining a margin based on a class angle between a first class vector of the first class and a second class vector of a second class, among the class vectors, and a feature angle between the feature vector and the first class vector; determining a loss value using a loss function including an angle with the margin applied to the feature angle and the plural feature angles; and training the neural network by updating, based on the loss value, either one or both of one or more parameters of the neural network and one or more of the class vectors.

Abstract: The present invention relates to a use of agar-derived oligosaccharides for inhibiting the growth of Staphylococcus. More specifically, the present invention provides, as a material for medicine, food, cosmetics and the like, a use of agar-derived agarooligosaccharides, agarobiose or AHG, which have an effect of inhibiting the growth of Staphylococcus or killing the same.

Abstract: A user authentication method and a user authentication apparatus acquire an input image including a frontalized face of a user, calculate a confidence map including confidence values, for authenticating the user, corresponding to pixels with values maintained in a depth image of the frontalized face of the user among pixels included in the input image, extract a second feature vector from a second image generated based on the input image and the confidence map, acquire a first feature vector corresponding to an enrolled image, and perform authentication of the user based on a correlation between the first feature vector and the second feature vector.

Abstract: A processor-implemented neural network method includes: determining, using a neural network, a feature vector based on a training image of a first class among a plurality of classes; determining, using the neural network, plural feature angles between the feature vector and class vectors of other classes among the plurality of classes; determining a margin based on a class angle between a first class vector of the first class and a second class vector of a second class, among the class vectors, and a feature angle between the feature vector and the first class vector; determining a loss value using a loss function including an angle with the margin applied to the feature angle and the plural feature angles; and training the neural network by updating, based on the loss value, either one or both of one or more parameters of the neural network and one or more of the class vectors.

Abstract: A processor-implemented method includes: generating a preprocessed infrared (IR) image by performing first preprocessing based on an IR image including an object; generating a preprocessed depth image by performing second preprocessing based on a depth image including the object; and determining whether the object is a genuine object based on the preprocessed IR image and the preprocessed depth image.

Abstract: An electronic apparatus and a booting method thereof are provided. The electronic apparatus includes an inputter configured to receive a power-on command, and a memory configured to store task-processing information of tasks for each booting mode. The electronic apparatus further includes a processor configured to, in response to the reception of the power-on command, determine a booting mode, based on use information of the electronic apparatus, determine a priority order and an affinity of each of the tasks for the determined booting mode, based on the task-processing information of the tasks for the determined booting mode, and process the tasks for the determined booting mode, based on the determined priority order and affinity of each of the tasks for the determined booting mode, to boot the electronic apparatus.

Abstract: An electronic apparatus and a booting method thereof are provided. The electronic apparatus includes an inputter configured to receive a power-on command, and a memory configured to store task-processing information of tasks for each booting mode. The electronic apparatus further includes a processor configured to, in response to the reception of the power-on command, determine a booting mode, based on use information of the electronic apparatus, determine a priority order and an affinity of each of the tasks for the determined booting mode, based on the task-processing information of the tasks for the determined booting mode, and process the tasks for the determined booting mode, based on the determined priority order and affinity of each of the tasks for the determined booting mode, to boot the electronic apparatus.