Samsung Electronics Co., Ltd.

Namjoon Kim

Kyuhong Kim

Sungjoo Suh

Sehwan Lee

Wonjun Kim

Chang Kyu Choi

Joonah Park

Jungsoon Shin

Soochul Lim

Jaejoon Han

Byungin Yoo

Changkyu Choi

Joonho Song

Changkyo Lee

Junwoo Jang

Deokjin Joo

Du-Sik Park

Hyungsuk Kim

Jaehyuk Choi

Tae-Sung Jung

Seokwhan Chung

Hyunjeong Lee

Byungkyu Lee

A neural network apparatus includes a plurality of node buffers connected to a node lane and configured to store input node data by a predetermined bit size; a plurality of weight buffers connected to a weight lane and configured to store weights; and one or more processors configured to: generate first and second split data by splitting the input node data by the predetermined bit size, store the first and second split data in the node buffers, output the first split data to an operation circuit for a neural network operation on an index-by-index basis, shift the second split data, and output the second split data to the operation circuit on the index-by-index basis.

Apparatus and method for processing convolution operation of neural network

Provided are a method and apparatus for processing a convolution operation in a neural network, the method includes determining operands from input feature maps and kernels, on which a convolution operation is to be performed, dispatching operand pairs combined from the determined operands to multipliers in a convolution operator, generating outputs by performing addition and accumulation operations with respect to results of multiplication operations, and obtaining pixel values of output feature maps corresponding to a result of the convolution operation based on the generated outputs.

Method and apparatus for processing convolution operation in neural network using sub-multipliers

A method of performing an operation in a neural network apparatus may include acquiring operation groups each comprising at least one input feature map and at least one kernel, and tag information corresponding to each of the operation groups, determining an operating unit in an idle state from among operating units, performing, at the operating unit in the idle state, a convolution operation between an input feature map and a kernel included in a operation group from among the operation groups to create an intermediate feature map, determining, based on tag information corresponding to the operation group, a post-processing unit from among post-processing units, and creating, at the post-processing unit, an output feature map using the intermediate feature map.

Apparatus and method for performing a recognition operation in a neural network

A processor-implemented method of performing convolution operations in a neural network includes generating a plurality of first sub-bit groups and a plurality of second sub-bit groups, respectively from at least one pixel value of an input feature map and at least one predetermined weight, performing a convolution operation on a first pair that includes a first sub-bit group including a most significant bit (MSB) of the at least one pixel value and a second sub-bit group including an MSB of the at least one predetermined weight, based on the plurality of second sub-bit groups, obtaining a maximum value of a sum of results for convolution operations of remaining pairs excepting the first pair, and based on a result of the convolution operation on the first pair and the maximum value, determining whether to perform the convolution operations of the remaining pairs.

Method and apparatus with neural network convolution operations

A method for updating biometric authentication data authenticates an input image using an enrollment database (DB) over a first length of time, the authentication including generating information for authenticating the input image, and updates the enrollment DB based on the first length time and the information for authenticating the input image.

Methods and apparatuses for updating user authentication data

A user authentication method using a fingerprint image, the user authentication method includes receiving at least a portion of a fingerprint image of a user; actuating a processor to divide the fingerprint image into a plurality of first sub-blocks; generate a set of input codes by encoding the first sub-blocks based on a coded model; measure a similarity between the set of the input codes and a set of registered codes included in a pre-registered binary codebook; and authenticate the user based on the similarity.

User authentication method using fingerprint image and method of generating coded model for user authentication

A fingerprint recognition method includes receiving an input partial image corresponding to a partial image of a fingerprint of a first user; partitioning the input partial image into a plurality of blocks; performing a comparison operation based on the plurality of blocks and the enrolled partial images corresponding to partial images of an enrolled fingerprint; and recognizing the fingerprint of the first user based on a result of the comparison operation.

Method and apparatus for recognizing fingerprint

An authentication method includes projecting a near infrared (NIR) ray using a light emitting diode (LED) of a terminal, receiving a light reflected by a vein of a user using an image sensor of the terminal, verifying whether an image generated using the received light exhibits a vein pattern, in response to the image generated using the received light being verified as exhibiting the vein pattern, generating a vein pattern of the vein based on an image generated using the received light, and in response to the generated vein pattern being determined to match a pre-stored vein pattern, authenticating the user as a registered user corresponding to the pre-stored vein pattern.

Method and apparatus with vein pattern authentication

Provided are a method of recognizing a fingerprint and a device including the same. The method of recognizing a fingerprint includes obtaining a fingerprint image from a fingerprint sensor, determining whether a pixel in the fingerprint image is defective based on a dispersion value of the pixel with respect to time, in response to determining that the pixel is defective, generating an interpolated pixel value of the pixel by performing interpolation on a first pixel value of the pixel based on a second pixel value of another pixel different from the pixel, and correcting the fingerprint image based on the interpolated pixel value.

Method of recognizing fingerprint and electronic device including the same

A fingerprint recognition method includes generating an enrollment modified image by modifying a fingerprint image corresponding to a fingerprint to be enrolled; extracting enrollment property information from the fingerprint image; generating mapping information that maps the enrollment modified image to the enrollment property information; and storing the enrollment modified image and the enrollment property information.

Fingerprint recognition method and apparatus

A method and apparatus for authenticating a user using a vein pattern are provided that project a near infrared (NIR) ray toward a skin of the user using a light emitting diode (LED), where the user is adjacent to a terminal including the LED. An image sensor receives a light reflected by the skin, generates a vein pattern of the skin based on an image generated using the received light, and authenticates the user as a registered user of a pre-stored vein pattern when the generated vein pattern matches the pre-stored vein pattern.

Method and apparatus for authenticating user using vein pattern

A method and an apparatus for extracting a facial feature and a method and an apparatus for recognizing a face are provided, in which the apparatus for extracting a facial feature may extract facial landmarks from a current input image, sample a skin region and a facial component region based on the extracted facial landmarks, generate a probabilistic model associated with the sampled skin region and the facial component region, extract the facial component region from a face region included in the input image using the generated probabilistic model, and extract facial feature information from the extracted facial component region.

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Anyang-si, South Korea

Namjoon Kim