Samsung Electronics Co., Ltd.

Lg Energy Solution, Ltd.

Insang Cho

Chanyoung Hwang

Wonjae Lee

Yongmin Tai

Daesung Cho

Kiwon Yoo

Jeong Soo Seol

Sung Kyum Kim

Eui Young Jung

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.

Electronic apparatus and controlling method thereof

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.

Processor chip and control methods thereof

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.

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.

Computing apparatus using convolutional neural network and method of operating the same

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.

Electronic apparatus and control method for updating parameters of neural networks while generating high-resolution images

An electronic apparatus includes a memory storing information on an artificial intelligence (AI) model comprising a plurality of layers, and a processor configured to obtain an output image that is processed from an input image using the AI model. The processor is configured to, based on a number of non-zero data values included in operation data output from a first layer among the plurality of layers, compress the operation data according to at least one of a plurality of coding modes and store the compressed data in an internal memory, obtain restoration data corresponding to the operation data by decompressing the compressed data stored in the internal memory, and provide the obtained restoration data to a second layer among the plurality of layers.

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.

Image processing apparatus and method of operating the same

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.

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Suwon-si, South Korea

Insang Cho