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. The apparatus for processing images according to an embodiment includes an image input unit configured to receive a first image of a Bayer pattern including noise and an image output unit configured to output a noise-removed image by removing noise from the first image using a noise removal model, and the noise removal model includes a color correlation block configured to generate a second image of the Bayer pattern including RGB correlation information about the first image from the first image by performing rearrange and convolution operations on the first image, a discrete cosine transform (DCT) block configured to generate a third image in which a high-frequency component of the first image is highlighted by applying a DCT to the first image, and one or more discrete wavelet transform (DWT) blocks configured to generate a low-frequency feature map and one or more high-frequency feature maps by applying a DWT to a first feature map generated based on the first image, the second image, and the third image, and generate a final feature map in which a high-frequency component and a low-frequency component of the first feature map are highlighted based on the low-frequency feature map and the one or more high-frequency feature maps.
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 greater or less than N; and (g) a step in which if the channel switched in step (0 is greater than N, the main controller determines that the convolution operation for all channels has been completed and outputs the feature map by means of a feature map output unit. By doing this, the convolution operation which occupies most of the convolution neural network is reduced to increase inference speed in the deep learning.
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:
The present disclosure a method of decoding a polar code based on a shared node, the method includes extracting an input node from target data that are data to be decoded, by an extractor, sorting the input node as one of a first node of which the pattern of the frozen bit satisfies a predetermined first reference, a second node of which the pattern of the information bit satisfies a predetermined second reference, and a third node that is not the first node and the second node, by a sorter, calculating at least one codeword candidate and at least one path metric that correspond to the input node in accordance with the sorting result by a calculator, finishing decoding the target data by iterating the extracting, the sorting as one, and the calculating of at least one path metric by a controller.
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:
Disclosed is a high efficiency video coding (HEVC) encoding device including a candidate group updater configured to select a plurality of representative modes as a candidate group from among intra-prediction modes and update the candidate group using a plurality of minimum modes selected from the candidate group, the plurality of representative modes each representing a range where there is an optimal mode, and an optimal mode selector configured to select any one mode as an optimal mode from among a plurality of minimum modes selected from the updated candidate group.