Samsung Electronics Co., Ltd.

Renesas Electronics Corporation

Ilhyun Cho

Jayoon Koo

Namuk Kim

Wookhyung Kim

Anant Baijal

Cheulhee Hahm

Daesung Cho

Kibeom Kim

Wooseok Kang

Rakie Kim

Soonwan Kwon

Keuntek Lee

Kwang-Seok Han

Soonseob Lee

Heewon Suh

Gilpyo Lee

An electronic device is provided. The electronic device includes a memory storing one or more instructions, and a processor configured to execute the one or more instruction stored in the memory. The processor is configured to execute the one or more instructions to obtain a subjective assessment score for each of a plurality of sub-regions included in an input frame, the subjective assessment score being a Mean Opinion Score (MOS); obtain a location weight for each of the plurality of sub-regions, the location weight indicating characteristics according to a location of a display; obtain a weighted assessment score for each of the plurality of sub-regions, based on the subjective assessment score for each of the plurality of sub-regions and the location weight for each of the plurality of sub-regions; and obtain a final quality score for the entire video frame, based on the weighted assessment score for each of the plurality of sub-regions.

Electronic device for performing video quality assessment, and operation method of the electronic device

An artificial intelligence (AI) upscaling apparatus for upscaling a low-resolution image to a high-resolution image includes: a memory storing one or more instructions; and a processor configured to execute the one or more instructions stored in the memory, wherein the processor is configured to: obtain a second image corresponding to a first image, which is downscaled from an original image by an AI downscaling apparatus by using a first deep neural network (DNN); and obtain a third image by upscaling the second image by using a second DNN corresponding to the first DNN, and wherein the second DNN is trained to minimize a difference between a first restored image, which results from applying no pixel movement to an original training image, and second restored images, which result from downscaling, upscaling, and subsequently retranslating one or more translation images obtained by applying pixel movement to the original training image.

AI downscaling apparatus and operating method thereof, and AI upscaling apparatus and operating method thereof

An operating method of a computing apparatus is provided. The operating method of the computing apparatus includes obtaining a reference image; obtaining a distorted image generated from a reference image; obtaining an objective quality assessment score of a distorted image that is indicative of a quality of a distorted image as assessed by an algorithm, by using a reference image and a distorted image; obtaining a subjective quality assessment score corresponding to a objective quality assessment score; and training a neural network, by using a distorted image and a subjective quality assessment score as a training data set.

Video quality assessment method and apparatus

A quadrature phase clock generator includes a tunable polyphase filter and a phase detector. The tunable polyphase filter is configured to receive an input clock signal and generate four quadrature phase clock signals. The phase detector is coupled to receive at least two of the four quadrature phase clock signals and generate a control signal adapted to tune the polyphase filter based on the received quadrature phase clock signals. Further, the phase detector is configured to provide the control signal to the polyphase filter in a feedback loop. Based on the control signal from the phase detector, the tunable polyphase filter generates four tuned quadrature phase clock signals as output phase clock signals.

Wideband quadrature phase generation using tunable polyphase filter

Provided are an image processing apparatus and method. The image processing apparatus includes a decoder configured to decode image frames of an image; an image quality controller configured to obtain a genre recognition confidence of a previous image frame and a genre recognition confidence of a current image frame, and identify image quality control factor value, based on the genre recognition confidence of the previous image frame and the genre recognition confidence of the current image frame; and an image quality processor configured to image-quality process at least one of the decoded image frames by using the image quality control factor value, and output the processed at least one of the decoded image frames.

Image processing apparatus and method thereof

A method for controlling performance of an electronic device is provided. The method includes sensing user input, predicting user input speed, and controlling at least one processing unit of the electronic device based on a predicted user input speed and performance assignment information. Here, the performance assignment information includes control information mapped respectively with user input speeds for controlling the at least one processing unit of the electronic device.

Method and apparatus for controlling performance of electronic device

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Seoul, South Korea

Ilhyun Cho