Abstract: A display device includes a plurality of pixel electrodes disposed on a substrate, an emission layer disposed on each of the plurality of pixel electrodes, a counter electrode disposed on the emission layer to correspond to the plurality of pixel electrodes, an insulating layer disposed on the counter electrode and including a trench corresponding to an area between the plurality of pixel electrodes, a light blocking material layer disposed in the trench, and a color filter layer disposed on the insulating layer and selectively transmitting light of a specific wavelength band.

Abstract: Disclosed in a processor chip configured to perform neural network processing. The processor chip includes a memory, a first processor configured to perform neural network processing on a data stored in the memory, a second processor and a third processor, and the second processor is configured to transmit a control signal to the first processor and the third processor to cause the first processor and the third processor to perform an operation.

Abstract: An electronic apparatus may include a memory that stores first information regarding a plurality of first artificial intelligence models trained to perform image processing differently from each other and second information regarding a second artificial intelligence model trained to identify a type of an image by predicting a processing result of the image by each of the plurality of first artificial intelligence models. The electronic apparatus may further include a processor configured to identify a type of an input image by inputting the input image to the second artificial intelligence model stored in the memory, and process the input image by inputting the input image to one of the plurality of first intelligence models stored in the memory based on the identified type.

Abstract: Disclosed in a processor chip configured to perform neural network processing. The processor chip includes a memory, a first processor configured to perform neural network processing on a data stored in the memory, a second processor and a third processor, and the second processor is configured to transmit a control signal to the first processor and the third processor to cause the first processor and the third processor to perform an operation.

Abstract: An apparatus and a method use a convolutional neural network (CNN) including a plurality of convolution layers in the field of artificial intelligence (AI) systems and applications thereof. A computing apparatus using a CNN including a plurality of convolution layers includes a memory storing one or more instructions; and one or more processors configured to execute the one or more instructions stored in the memory to obtain input data; identify a filter for performing a convolution operation with respect to the input data, on one of the plurality of convolution layers; identify a plurality of sub-filters corresponding to different filtering regions within the filter; provide a plurality of feature maps based on the plurality of sub-filters; and obtain output data, based on the plurality of feature maps.

Abstract: Disclosed is an electronic apparatus. The electronic apparatus includes: a memory configured to store information regarding an artificial intelligence model including a plurality of layers; and a processor configured to perform interpolation processing on an input image and to process the interpolated image using the artificial intelligence model to obtain an output image, wherein the processor is configured to be operated in a first mode or a second mode based on an update of parameters used in at least one of the plurality of layers being required, the first mode including a mode in which the output image is obtained based on an image processed using the artificial intelligence model in which the parameters are updated and based on the interpolated image, and the second mode includes a mode in which the output image is obtained based on the interpolated image.

Abstract: An electronic apparatus may include a memory that stores first information regarding a plurality of first artificial intelligence models trained to perform image processing differently from each other and second information regarding a second artificial intelligence model trained to identify a type of an image by predicting a processing result of the image by each of the plurality of first artificial intelligence models. The electronic apparatus may further include a processor configured to identify a type of an input image by inputting the input image to the second artificial intelligence model stored in the memory, and process the input image by inputting the input image to one of the plurality of first intelligence models stored in the memory based on the identified type.

Abstract: An electronic apparatus is provided. The electronic apparatus includes a memory storing information on a first artificial intelligence model for identifying a type of an object included in an image and information on a plurality of second artificial intelligence models for upscaling the image and a processor connected to the memory and configured to control the electronic apparatus, and the processor is configured to input an input image to the first artificial intelligence model and identify a type of an object included in the input image, and upscale the input image by inputting the input image to one of the plurality of second artificial intelligence models based on the identified type of the object.

Abstract: An electronic apparatus may include a memory that stores first information regarding a plurality of first artificial intelligence models trained to perform image processing differently from each other and second information regarding a second artificial intelligence model trained to identify a type of an image by predicting a processing result of the image by each of the plurality of first artificial intelligence models. The electronic apparatus may further include a processor configured to identify a type of an input image by inputting the input image to the second artificial intelligence model stored in the memory, and process the input image by inputting the input image to one of the plurality of first intelligence models stored in the memory based on the identified type.

Abstract: Disclosed is an electronic apparatus. The electronic apparatus includes: a memory configured to store information regarding an artificial intelligence model including a plurality of layers; and a processor configured to perform interpolation processing on an input image and to process the interpolated image using the artificial intelligence model to obtain an output image, wherein the processor is configured to be operated in a first mode or a second mode based on an update of parameters used in at least one of the plurality of layers being required, the first mode including a mode in which the output image is obtained based on an image processed using the artificial intelligence model in which the parameters are updated and based on the interpolated image, and the second mode includes a mode in which the output image is obtained based on the interpolated image.

Abstract: An image processing apparatus processes an image by using one or more neural networks, and includes a memory storing one or more instructions and data structures for a main neural network and a sub-neural network, and a processor configured to execute the one or more instructions stored in the memory to process an input image by using the main neural network to obtain intermediate result data and a final output image, and to process the intermediate result data by using the sub-neural network to output an intermediate image while the input image is being processed by using the main neural network.

Abstract: Disclosed is an electronic apparatus. The electronic apparatus includes: a memory configured to store information regarding an artificial intelligence model including a plurality of layers; and a processor configured to perform interpolation processing on an input image and to process the interpolated image using the artificial intelligence model to obtain an output image, wherein the processor is configured to be operated in a first mode or a second mode based on an update of parameters used in at least one of the plurality of layers being required, the first mode including a mode in which the output image is obtained based on an image processed using the artificial intelligence model in which the parameters are updated and based on the interpolated image, and the second mode includes a mode in which the output image is obtained based on the interpolated image.

Abstract: Disclosed is an electronic apparatus. The electronic apparatus includes: a memory configured to store information regarding an artificial intelligence model including a plurality of layers; and a processor configured to perform interpolation processing on an input image and to process the interpolated image using the artificial intelligence model to obtain an output image, wherein the processor is configured to be operated in a first mode or a second mode based on an update of parameters used in at least one of the plurality of layers being required, the first mode including a mode in which the output image is obtained based on an image processed using the artificial intelligence model in which the parameters are updated and based on the interpolated image, and the second mode includes a mode in which the output image is obtained based on the interpolated image.

Abstract: An electronic device and a method for controlling the same include inputting an input image into an artificial intelligence model, acquiring a feature map for the input image, converting the feature map through a lookup table corresponding to the feature map, and storing the converted feature map by compressing the feature map through a compression mode corresponding to the feature map.

Abstract: An electronic apparatus may include a memory that stores first information regarding a plurality of first artificial intelligence models trained to perform image processing differently from each other and second information regarding a second artificial intelligence model trained to identify a type of an image by predicting a processing result of the image by each of the plurality of first artificial intelligence models. The electronic apparatus may further include a processor configured to identify a type of an input image by inputting the input image to the second artificial intelligence model stored in the memory, and process the input image by inputting the input image to one of the plurality of first intelligence models stored in the memory based on the identified type.

Abstract: Disclosed is an electronic apparatus. The electronic apparatus includes: a memory configured to store information regarding an artificial intelligence model including a plurality of layers; and a processor configured to perform interpolation processing on an input image and to process the interpolated image using the artificial intelligence model to obtain an output image, wherein the processor is configured to be operated in a first mode or a second mode based on an update of parameters used in at least one of the plurality of layers being required, the first mode including a mode in which the output image is obtained based on an image processed using the artificial intelligence model in which the parameters are updated and based on the interpolated image, and the second mode includes a mode in which the output image is obtained based on the interpolated image.

Abstract: Disclosed in a processor chip configured to perform neural network processing. The processor chip includes a memory, a first processor configured to perform neural network processing on a data stored in the memory, a second processor and a third processor, and the second processor is configured to transmit a control signal to the first processor and the third processor to cause the first processor and the third processor to perform an operation.

Abstract: Disclosed in a processor chip configured to perform neural network processing. The processor chip includes a memory, a first processor configured to perform neural network processing on a data stored in the memory, a second processor and a third processor, and the second processor is configured to transmit a control signal to the first processor and the third processor to cause the first processor and the third processor to perform an operation.

Abstract: An image processing apparatus processes an image by using one or more neural networks, and includes a memory storing one or more instructions and data structures for a main neural network and a sub-neural network, and a processor configured to execute the one or more instructions stored in the memory to process an input image by using the main neural network to obtain intermediate result data and a final output image, and to process the intermediate result data by using the sub-neural network to output an intermediate image while the input image is being processed by using the main neural network.

Abstract: An electronic device and a method for managing memory thereof are disclosed. According to an embodiment of the present disclosure, a method for an electronic device to manage memory, comprising: determining whether a physical address mapped to a virtual address is consecutive with respect to at least two entries belonging to a plurality of entries having virtual addresses and physical addresses mapped and including a consecutive virtual address; merging entries in which the virtual address and the physical address are consecutive into one entry if, as a result of the determination, the physical addresses of the at least entries are consecutive; and storing the merged entry in first memory.