Abstract: A display device includes a display area and a peripheral area surrounding the display area, a pixel disposed in the display area on a substrate, an insulating layer disposed on the substrate and having a valley part along a periphery of the display area in the peripheral area, and an emission driver disposed in the peripheral area on the substrate, providing an emission signal to the pixel through an emission line, and overlapping both a first inner surface and a second inner surface of the insulating layer of the valley part in a plan view.

Abstract: A display device includes a base layer, a first conductive layer disposed on the base layer, an inorganic layer disposed on the first conductive layer, a first semiconductor layer including an oxide semiconductor and disposed on the inorganic layer, and a first insulation layer disposed on the first semiconductor layer, a second semiconductor layer including an oxide semiconductor, and disposed on the first insulation layer, wherein the first conductive layer is a first electrode of a first capacitor, the first semiconductor layer is a second electrode of the first capacitor and a first electrode of a second capacitor, and the second semiconductor layer is a second electrode of the second capacitor.

Abstract: Provided are an object detection system and an object detection method. An object detection system may include a feature map extraction module configured to receive an image for object detection and extract a feature map having multiple resolutions for the image; a bounding box detection module configured to classify a bounding box by applying a first group of convolutional layers to the feature map, and predict the bounding box by applying a second group of convolutional layers to the feature map; and a mask generation module configured to generate a mask for the shape of the object in the bounding box using the feature map.

Abstract: A method and apparatus for face recognition robust to an alignment of the face comprising: estimating prior information of a facial shape from an input image cropped from an image including a face using the first deep neural network (DNN); extracting feature information of facial appearance from the input image by using a second DNN; training, by using a face image decoder based on the prior information and the feature information, the face recognition apparatus; and extracting, from a test image, facial shape-aware features in the inference step by using the trained second DNN.

Abstract: Provided are an object detection system and an object detection method. An object detection system may include a feature map extraction module configured to receive an image for object detection and extract a feature map having multiple resolutions for the image; a bounding box detection module configured to classify a bounding box by applying a first group of convolutional layers to the feature map, and predict the bounding box by applying a second group of convolutional layers to the feature map; and a mask generation module configured to generate a mask for the shape of the object in the bounding box using the feature map.