Abstract: A display device and method for manufacturing thereof are provided. The display device includes a substrate having a display area and a non-display area, and including an edge, an upper surface having an edge area in which a processing trace remains adjacent to the edge, a bottom surface opposite to the upper surface, a side surface connected to the upper surface and not parallel thereto, and a first inclined surface connected to the side surface and to the bottom surface, a light-emitting element layer above the upper surface of the substrate in the display area, and including light-emitting elements, an encapsulating layer above the light-emitting element layer and corresponding to a portion of the display area and the non-display area, and a protective layer above an outer surface of the substrate, and located on at least one of the bottom surface, the side surface, or the first inclined surface.

Abstract: A display device includes: a substrate including a display area and a non-display area surrounding the display area; a light emitting element layer on the display area on the substrate and including a plurality of light emitting elements; and an encapsulating layer on the light emitting element layer and on a portion of the display area and the non-display area; and wherein the substrate comprises an upper surface on which the light emitting element layer is located, a bottom surface opposite to the upper surface, a side surface connected to the upper surface and not parallel to the upper surface, and a first inclined surface connected to the side surface and the bottom surface and not parallel to the side surface and the bottom surface, wherein an edge area of the upper surface of the substrate adjacent to an edge of the substrate, in which a processing trace remains.

Abstract: A display device includes: a substrate comprising an upper surface, a bottom surface facing the upper surface, and a through hole penetrating the upper surface and the bottom surface; and a light emitting element layer on the upper surface of the substrate, wherein the substrate comprises a side surface that meets the upper surface in the through hole, a first surface that meets the bottom surface, a second surface that meets the side surface, and a third surface between the first surface and the second surface, and wherein the first surface and the second surface are spaced apart from each other with the third surface therebetween, and are inclined surfaces.

Abstract: An electronic device includes a display device, which may be fabricated using a described method. The display device includes a glass substrate including a first surface, a second surface opposite the first surface, and a side surface between the first surface and the second surface, an outermost structure on the first surface of the glass substrate and located adjacent to an edge of one side of the glass substrate, and a display area including a plurality of light emitting areas on the first surface of the glass substrate and located farther from the edge of the one side of the glass substrate than the outermost structure is. A minimum distance from the side surface of the glass substrate to the outermost structure is equal to 130 ?m or less.

Abstract: An image processing apparatus and an image processing method for estimating a region of interest based on information of interest learned by a data recognition model satisfying a certain condition from among a plurality of data recognition models and for setting a focus are provided. The image processing apparatus includes estimating a region of interest by using a rule-based algorithm or an artificial intelligence (AI) algorithm. When estimating a region of interest by using an AI algorithm, the image processing apparatus may estimate a region of interest by using a machine learning algorithm, a neural network algorithm, or a deep learning algorithm.

Abstract: Provided is an artificial intelligence (AI) system for simulating human brain functions such as perception and judgment by using a machine learning algorithm such as deep learning, and an application thereof. Provided is a device and method for recommending products to a user on the basis of facial expression information of the user through the AI system. The method, performed by the device, of recommending products includes: displaying a product selected by the user; obtaining user's facial expression information with respect to the displayed product; determining the user's satisfaction with the displayed product based on the obtained user's facial expression information; selecting a product set to be recommended to the user from among a plurality of product sets based on the determined user's satisfaction; and displaying at least one product included in the selected product set.

Abstract: An image processing apparatus and an image processing method for estimating a region of interest based on information of interest learned by a data recognition model satisfying a certain condition from among a plurality of data recognition models and for setting a focus are provided. The image processing apparatus includes estimating a region of interest by using a rule-based algorithm or an artificial intelligence (AI) algorithm. When estimating a region of interest by using an AI algorithm, the image processing apparatus may estimate a region of interest by using a machine learning algorithm, a neural network algorithm, or a deep learning algorithm.

Abstract: An image processing apparatus and an image processing method for estimating a region of interest based on information of interest learned by a data recognition model satisfying a certain condition from among a plurality of data recognition models and for setting a focus are provided. The image processing apparatus includes estimating a region of interest by using a rule-based algorithm or an artificial intelligence (AI) algorithm. When estimating a region of interest by using an AI algorithm, the image processing apparatus may estimate a region of interest by using a machine learning algorithm, a neural network algorithm, or a deep learning algorithm.

Abstract: An electronic apparatus is provided. The electronic apparatus includes at least one processor configured to detect, by a sensor, a driving state of a vehicle or a driving state of another vehicle in a vicinity of the vehicle while the vehicle is being driven, obtain state data including the driving state of the vehicle and the driving state of the other vehicle, and use at least one data recognition model to determine a dangerous situation of the vehicle after a certain period of time while the vehicle is being driven, based on the obtained state data. The electronic apparatus may predict a dangerous situation of the vehicle by using a rule-based algorithm or an artificial intelligence (AI) algorithm. The electronic apparatus predicts the dangerous situation of the vehicle by using at least one of machine learning, a neural network, and a deep learning algorithm.

Abstract: An electronic apparatus is provided. The electronic apparatus includes at least one processor configured to detect, by a sensor, a driving state of a vehicle or a driving state of another vehicle in a vicinity of the vehicle while the vehicle is being driven, obtain state data including the driving state of the vehicle and the driving state of the other vehicle, and use at least one data recognition model to determine a dangerous situation of the vehicle after a certain period of time while the vehicle is being driven, based on the obtained state data. The electronic apparatus may predict a dangerous situation of the vehicle by using a rule-based algorithm or an artificial intelligence (AI) algorithm. The electronic apparatus predicts the dangerous situation of the vehicle by using at least one of machine learning, a neural network, and a deep learning algorithm.

Abstract: Provided is an artificial intelligence (AI) system for simulating human brain functions such as perception and judgment by using a machine learning algorithm such as deep learning, and an application thereof. Provided is a device and method for recommending products to a user on the basis of facial expression information of the user through the AI system. The method, performed by the device, of recommending products includes: displaying a product selected by the user; obtaining user's facial expression information with respect to the displayed product; determining the user's satisfaction with the displayed product based on the obtained user's facial expression information; selecting a product set to be recommended to the user from among a plurality of product sets based on the determined user's satisfaction; and displaying at least one product included in the selected product set.

Abstract: The present disclosure relates to an artificial intelligence (AI) system utilizing a machine learning algorithm such as deep learning, and application of the same. In particular, a method for controlling an electronic device of the present disclosure comprises the steps of: obtaining image data and supplementary data including data on a user from an external terminal connected to the electronic device; generating feature data for determining the user's actual emotion by using the image data and the supplementary data; and determining the user's actual emotion by inputting the feature data into an emotion recognition model.

Abstract: An image processing apparatus and an image processing method for estimating a region of interest based on information of interest learned by a data recognition model satisfying a certain condition from among a plurality of data recognition models and for setting a focus are provided. The image processing apparatus includes estimating a region of interest by using a rule-based algorithm or an artificial intelligence (AI) algorithm.

Abstract: An electronic apparatus is provided. The electronic apparatus includes at least one processor configured to detect, by a sensor, a driving state of a vehicle or a driving state of another vehicle in a vicinity of the vehicle while the vehicle is being driven, obtain state data including the driving state of the vehicle and the driving state of the other vehicle, and use at least one data recognition model to determine a dangerous situation of the vehicle after a certain period of time while the vehicle is being driven, based on the obtained state data. The electronic apparatus may predict a dangerous situation of the vehicle by using a rule-based algorithm or an artificial intelligence (AI) algorithm. The electronic apparatus predicts the dangerous situation of the vehicle by using at least one of machine learning, a neural network, and a deep learning algorithm.