Abstract: A display device includes a via insulating layer on a substrate; a first electrode on the via insulating layer; a pixel defining layer including an inclined region on the first electrode and including a first opening exposing a portion of the first electrode, and a flat region at a side of the inclined region and in contact with the via insulating layer; a light emitting layer on the portion of the first electrode exposed by the first opening; organic particles on the flat region of the pixel defining layer; an encapsulation layer covering the pixel defining layer, the light emitting layer, and the organic particles, and including a first layer, a second layer, and a third layer; and a first light blocking layer on the third layer of the encapsulation layer to overlap the flat region of the pixel defining layer and form a second opening.

Abstract: A system and a method for detecting image forgery through a convolutional neural network are capable of detecting image manipulation of compressed and/or color images. The system comprises a manipulated feature pre-processing unit applying an input image to a high-pass filter to enhance features due to image forgery; a manipulated feature extraction unit extracting image manipulated feature information from the image with the enhanced features through a pre-trained convolutional neural network; a feature refining unit refining the extracted image manipulated feature information; and a manipulation classifying unit determining the image forgery based on the image manipulated feature information refined by the feature refining unit.

Abstract: A method for providing data associated with a shopping mall web page includes accessing a review item written by a user ID in association with the shopping mall web page, the review item including an image and a text; detecting at least one target object from the image included in the review item; processing the detected target object to generate first feature data; processing a reference object included in the shopping mall web page to generate second feature data corresponding to the reference object; and outputting verification data indicating a result of verification for the review item by comparing the first feature data, generated by processing the target object, with the second feature data, generated by processing the reference object.

Abstract: Provided is a system and method for creating and providing a mosaic image based on an image tag-word by a mosaic service providing server, which includes: determining each tag-word for each image and classifying a plurality of images according to the determined tag-word; determining a target image among the plurality of images; providing a pixel image selection interface for selecting a pixel image for mosaicizing the determined target image based on the tag-words of the plurality of images; and creating a mosaic image for the target image based on the pixel image selected through the pixel image selection interface.

Abstract: Provided is a system and method for creating and providing a mosaic image based on an image tag-word by a mosaic service providing server, which includes: determining each tag-word for each image and classifying a plurality of images according to the determined tag-word; determining a target image among the plurality of images; providing a pixel image selection interface for selecting a pixel image for mosaicizing the determined target image based on the tag-words of the plurality of images; and creating a mosaic image for the target image based on the pixel image selected through the pixel image selection interface.

Abstract: A system and a method for detecting image forgery through a convolutional neural network are capable of detecting image manipulation of compressed and/or color images. The system comprises a manipulated feature pre-processing unit applying an input image to a high-pass filter to enhance features due to image forgery; a manipulated feature extraction unit extracting image manipulated feature information from the image with the enhanced features through a pre-trained convolutional neural network; a feature refining unit refining the extracted image manipulated feature information; and a manipulation classifying unit determining the image forgery based on the image manipulated feature information refined by the feature refining unit.