Nota, Inc.

Myungsu Chae

Dong Wook Kim

Sung Hyun Kim

Young Seok Kim

Jaehun Kim

Seul Ki Yeom

KyungHwan Shim

Hye Rin Yoo

Chih Yuan Hsieh

Seong Un Hong

Dae-Woong Jeong

Sang Tae Kim

The effective network compression using simulation-guided iterative pruning according to various embodiments, can be configured so that, by means of an electronic device, a first neural network is pruned on the basis of a threshold value, a second neural network is generated, a gradient for each weighted value of the second neural network is calculated, and a third neural is acquired by applying the gradient to the first neural network.

Effective network compression using simulation-guided iterative pruning

Disclosed are a method and apparatus for continuous authentication. An authentication method includes receiving image frames taken by a camera in succession, detecting a face area in the image frames, tracking a change in a location of the detected face area in the image frames, and performing continuous user authentication for the face area according to the change in the location by using the face area whose change in the location has been tracked and a deep learning model.

Method and apparatus for continuous authentication

Disclosed are a method and apparatus for real-time on-device authentication based on deep learning. A deep learning-based authentication method includes detecting a location of a region of interest (ROI) occupied by a face portion an input image by using a detection model, extracting a feature map from the input image by using a feature extractor of the detection model, extracting a fixed length feature for the face portion using the feature map and ROI pooling for the detected location of the ROI, and classifying a face included in the input image based on the fixed length feature.

Method and apparatus for deep learning-based real-time on-device authentication

Disclosed is a technology for de-identifying and restoring personal information in an image based on an encryption key. An image processing method for de-identifying and restoring image information, which is performed by an image processing system, may include detecting an object information area in image information, de-identifying the detected object information area by using an encryption key generated in relation to the detected object information area, and restoring the de-identified object information area by using the encryption key.

Technology for de-identifying and restoring personal information in encryption key-based image

Disclosed are a method and apparatus for energy-aware deep neural network compression. A network pruning method for deep neural network compression includes measuring importance scores of a network unit by using an energy-based criterion with respect to a deep learning model, and performing network pruning of the deep learning model based on the importance scores.

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Daejeon, South Korea

Myungsu Chae