Abstract: The present invention relates to a breast image analysis method with four mammogram images which are input to a convolutional neural network as one input and a system therefor and the system includes an image receiving unit which receives four mammogram images; an image size adjusting unit which adjusts a size of a mammogram image received from the image receiving unit; a preprocessing unit which performs preprocessing on the mammogram image adjusted by the image size adjusting unit; a convolutional neural network (CNN)-based CNN learning unit which generates learning information by learning the mammogram image preprocessed by the preprocessing unit; and a CNN inference unit which receives the learning information learned from the CNN learning unit and a mammogram image to be classified from the image receiving unit to diagnose a breast abnormality.

Abstract: Disclosed are a method and apparatus for generating a decoding position control signal for decoding using polar codes. The method and apparatus for generating a decoding position control signal for decoding using polar codes according to an embodiment of the present disclosure include generating a decoding tree obtained by forming a plurality of nodes in a hierarchical structure for a polar-encoded codeword, decoding the codeword using a successive cancellation (SC) decoding technique, and generating control signal through a preset operation relationship based on a position of a bit returned during re-decoding among the decoded codeword.

Abstract: Disclosed are an apparatus and method for successive cancellation flip decoding of a polar code. The apparatus for successive cancellation flip decoding of a polar code according to an embodiment includes an iterative unit subtotal matrix generator configured to generate an iterative unit subtotal matrix corresponding to a preset iterative unit size based on a portion of an entire subtotal matrix, a selection logic configured to determine one or more selection bits based on a bit string representing a position of a bit returned when re-decoding and generate an auxiliary matrix for generating the entire subtotal matrix from the one or more selection bits, and an entire subtotal matrix generator configured to generate the entire subtotal matrix by using the iterative unit subtotal matrix and the auxiliary matrix.

Abstract: A polar code decoding apparatus according to an embodiment includes a divider configured to generate a decoding tree in which a plurality of nodes including one or more critical sets for a polar-encoded codeword are formed in a hierarchical structure, and divide the decoding tree into one or more partitions, each partition equally including lowest nodes of the decoding tree, a determiner configured to determine a memory size for storing a primary decoding result based on a specific partition, the specific partition being selected from among the one or more partitions based on the number of critical sets included in each partition, and a decoder configured to decode the codeword primarily by using a successive cancellation (SC) decoding technique.

Abstract: Disclosed are a method for providing the necessary information for a diagnosis of Alzheimer's disease and an apparatus for executing the method. The apparatus for executing the method for providing the necessary information for a diagnosis of Alzheimer's disease includes one or more processors, a memory, and one or more programs, in which the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs includes an instruction for acquiring a photographed image of a patient's eyeball, an instruction for preprocessing the photographed image, generating a blood vessel image from the pre-processed photographed image using machine learning-based technology, and providing the necessary information for a diagnosis of Alzheimer's disease based on the generated blood vessel image, and an instruction for generating diagnostic prediction information based on the necessary information for a diagnosis of Alzheimer's disease.

Abstract: An apparatus for inserting an error correction code according to an embodiment includes an identifier configured to identify a plurality of critical sets included in a codeword generated using a polar code, based on the number of information bits and a total code length of the codeword, a divider configured to divide the codeword into a plurality of partitions, and an inserter configured to insert an error correction code into each of the divided partitions based on a distribution position of each of the plurality of critical sets.

Abstract: Disclosed are a method and apparatus for generating a decoding position control signal for decoding using polar codes. The method and apparatus for generating a decoding position control signal for decoding using polar codes according to an embodiment of the present disclosure include generating a decoding tree obtained by forming a plurality of nodes in a hierarchical structure for a polar-encoded codeword, decoding the codeword using a successive cancellation (SC) decoding technique, and generating control signal through a preset operation relationship based on a position of a bit returned during re-decoding among the decoded codeword.

Abstract: A method for decoding a signal encoded with polar codes by a decoding system is provided. The method comprises receiving, from a transmission system, a signal in which a plurality of cyclic redundancy checks (CRCs) are encoded by the polar codes, the plurality of CRCs being inserted into positions determined based on a plurality of information bits, a number of the plurality of information bits and a total code length, and decoding a code section including bits ranging from a first bit of the signal to a position where a last bit of a first CRC is inserted. The method further comprises re-performing successive cancellation flip decoding for the decoded code section, or determining whether to decode a next code section adjacent to the decoded code section, based on whether a CRC is detected in the decoded code section.

Abstract: Disclosed are an apparatus and method for successive cancellation flip decoding of a polar code. The apparatus for successive cancellation flip decoding of a polar code according to an embodiment includes an iterative unit subtotal matrix generator configured to generate an iterative unit subtotal matrix corresponding to a preset iterative unit size based on a portion of an entire subtotal matrix, a selection logic configured to determine one or more selection bits based on a bit string representing a position of a bit returned when re-decoding and generate an auxiliary matrix for generating the entire subtotal matrix from the one or more selection bits, and an entire subtotal matrix generator configured to generate the entire subtotal matrix by using the iterative unit subtotal matrix and the auxiliary matrix.

Abstract: There are disclosed an apparatus and method for processing images.

Abstract: A polar code decoding apparatus according to an embodiment includes a divider configured to generate a decoding tree in which a plurality of nodes including one or more critical sets for a polar-encoded codeword are formed in a hierarchical structure, and divide the decoding tree into one or more partitions, each partition equally including lowest nodes of the decoding tree, a determiner configured to determine a memory size for storing a primary decoding result based on a specific partition, the specific partition being selected from among the one or more partitions based on the number of critical sets included in each partition, and a decoder configured to decode the codeword primarily by using a successive cancellation (SC) decoding technique.

Abstract: An apparatus for inserting an error correction code according to an embodiment includes an identifier configured to identify a plurality of critical sets included in a codeword generated using a polar code, based on the number of information bits and a total code length of the codeword, a divider configured to divide the codeword into a plurality of partitions, and an inserter configured to insert an error correction code into each of the divided partitions based on a distribution position of each of the plurality of critical sets.

Abstract: A convolution method for high speed deep learning according to the present invention includes (a) a step in which a feature map receiving unit of the convolution system receives a feature map configured by N channels; (b) a step in which a main controller of the convolution system selects a “0”-th channel from the feature map configured by N channels; (c) a step in which the main controller confirms a coordinate in which x, y coordinate is “0”, from the feature map of the “0”-th channel; (d) a coarse step in which a convolution calculating unit of the convolution system performs a convolution operation and a rectified linear unit (ReLU) operation while shifting by 2 in a horizontal direction and a vertical direction in the feature map; (e) a step in which the channel switching unit of the convolution system switches the channel to a subsequent channel when the coarse step is completed for the feature map of the “0”-th channel; (g) a step in which the main controller determines whether the switched channel is

Abstract: An apparatus for generating an HDR image includes an input image generator that generates a first image and a second image and an HDR image generator that generates a high dynamic range (HDR) in which a dynamic range of an original image is extended from the first image and the second image using a pre-trained model including a first neural network, a second neural network, and a third neural network, in which the first neural network is pre-trained to output a third image, the second neural network is pre-trained to output a fourth image and the third neural network is pre-trained to generate the HDR image based on the third image and the fourth image.

Abstract: The present invention relates to a breast image analysis method with four mammogram images which are input to a convolutional neural network as one input and a system therefor and the system includes an image receiving unit which receives four mammogram images; an image size adjusting unit which adjusts a size of a mammogram image received from the image receiving unit; a preprocessing unit which performs preprocessing on the mammogram image adjusted by the image size adjusting unit; a convolutional neural network (CNN)-based CNN learning unit which generates learning information by learning the mammogram image preprocessed by the preprocessing unit; and a CNN inference unit which receives the learning information learned from the CNN learning unit and a mammogram image to be classified from the image receiving unit to diagnose a breast abnormality.

Abstract: A method for decoding a signal encoded with polar codes by a decoding system is provided. The method comprises receiving, from a transmission system, a signal in which a plurality of cyclic redundancy checks (CRCs) are encoded by the polar codes, the plurality of CRCs being inserted into positions determined based on a plurality of information bits, a number of the plurality of information bits and a total code length, and decoding a code section including bits ranging from a first bit of the signal to a position where a last bit of a first CRC is inserted. The method further comprises re-performing successive cancellation flip decoding for the decoded code section, or determining whether to decode a next code section adjacent to the decoded code section, based on whether a CRC is detected in the decoded code section.

Abstract: Disclosed are a method and an apparatus for jaundice diagnosis based on an image. The method for jaundice diagnosis based on an image includes: receiving a jaundice diagnostic image acquired by photographing both a specific body part of a user and a reference object at a place where the user is positioned at present; generating color distortion information indicating a color distortion degree of the reference object included in the jaundice diagnostic image; generating a jaundice diagnostic correction image by correcting color distortion of the jaundice diagnostic image based on the color distortion information; and diagnosing a jaundice symptom for the user by using the jaundice diagnostic correction image.

Abstract: As a method for diagnosing jaundice of a user based on an image by a jaundice diagnosis device, a jaundice diagnosis image is obtained including a jaundice diagnosis reference device divided into a first area and a second area, and a specific body part of a user located in the first area. The identification information of the jaundice diagnosis reference device inserted in the second area is extracted, and validity authentication of the identification information is requested through an interlocked authentication system. When the validity authentication success message is received from the authentication system, the user is diagnosed with jaundice based on the image of a specific body part located in the first area and the jaundice diagnosis comparison image included in the second area.

Abstract: Disclosed are image based jaundice analyzing method and apparatus. The image based jaundice analyzing method according to an exemplary embodiment of the present disclosure includes: receiving an image for jaundice diagnosis obtained by photographing a specific body part of a user and a reference object in a location where the user is currently located; generating color distortion information representing a degree of color distortion of the reference object included in the image for jaundice diagnosis; generating a correction image for jaundice diagnosis by correcting the color distortion of the image for jaundice diagnosis based on the color distortion information; and diagnosing a jaundice symptom of the user using the correction image for jaundice diagnosis.

Abstract: As a capsule endoscope control method in a receiving device interworking with the capsule endoscope, it is determined whether a lesion is detected in the digestive organ from the digestive organ image, upon receiving a digestive organ image for a digestive organ taken by the capsule endoscope. Depending on whether a lesion is detected and whether the digestive organ falls within a predetermined region of interest, a control signal is generated so that the capsule endoscope operates in one of a plurality of modes and transmitted to the capsule endoscope. Then, the capsule endoscope is controlled to capture the digestive organ in one of the plurality of modes.