• 한국실내디자인학회논문집
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• 제17권6호
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• pp.71-81
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• 2008

The purposes of this research are to correctly understand the relationship between a visual communication structure and a semantic communication structure when integrating and changing various architectural visual information. This study will classify various diagrams, which have been actively applied to the works of Rem Koolhaas and MVRDV when designing architecture, and based on the classification, it will analyze how the expression viewpoints inherent in the diagrams are changed and applied to processing and changing architectural visual information. The transformal usage of the visual information of architectural diagrams is classified into an analysis-centered processing method and a concept-centered processing method, and the characteristics of their usage are analyzed. The former shows an observer-centered expression viewpoint which effectively delivers an architect's analyzed architectural information or intent to a customer or an observer. It also allows an easy perception of the analyzed data, and uses qualitative expression viewpoints. The method combines systematic expression viewpoints, which value a relationship with visual information, and various architectural visual information; uses the combined expression viewpoints as one diagram for delivering various information simultaneously and for changing visual information. The latter shows author-centered subjective expression viewpoints, which are different from reproduction-centered fixed expression viewpoints. This method uses arbitrary expression viewpoints that overly extort, change or manipulate visual information. It shows simultaneous expression viewpoints that integrate various architectural visual information via omniscient expression viewpoints, such as reversing or projecting the points of viewing subjects, which human beings cannot perceive.

• Journal of information and communication convergence engineering
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• 제17권1호
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• pp.14-20
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• 2019

Currently, microarray gene expression data take advantage of the sufficient classification of cancers, which addresses the problems relating to cancer causes and treatment regimens. However, the sample size of gene expression data is often restricted, because the price of microarray technology on studies in humans is high. We propose enhancing the gene expression classification of support vector machines with generative adversarial networks (GAN-SVMs). A GAN that generates new data from original training datasets was implemented. The GAN was used in conjunction with nonlinear SVMs that efficiently classify gene expression data. Numerical test results on 20 low-sample-size and very high-dimensional microarray gene expression datasets from the Kent Ridge Biomedical and Array Expression repositories indicate that the model is more accurate than state-of-the-art classifying models.

• 한국실내디자인학회논문집
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• 제19권1호
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• pp.75-84
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• 2010

This study will establish the transformal characteristics of architectural visual information by investigating: how contemporary architects perceive and process multifaceted architectural information via the expression media since 1970s. The purposes and results of this study are summarized as follows: This study established the contemporary transformal characteristics by comparing the expression methods of traditional architects with the transformal characteristics of visual information derived from the contemporary architectural expression media. In a pluralistic information society, the expression methods of the past, which recognize space as a stationary, unidimensional visual point on a drawing surface, is now changing to the mixed, multidimensional expression methods that connect various visual points on a limited drawing surface. Furthermore, the rapid advancement of digital media is changing, from a method which simply arranges visual information, to a flexible visual tool which can process architecture sequentially and simultaneously. As the communication structure of architecture is moving toward an individual-centered two-way communication type, the information delivery method is used to visualize conceptual, inferential information, rather than visualizing realistic information which simply records facts. In the past, multidimensional, non-linear forms could not be processed by the conventional design processes and sketch work, but now they can be expressed via digital media.

• Journal of Information Processing Systems
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• 제17권3호
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• pp.556-570
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• 2021

The existing video expression recognition methods mainly focus on the spatial feature extraction of video expression images, but tend to ignore the dynamic features of video sequences. To solve this problem, a multi-mode convolution neural network method is proposed to effectively improve the performance of facial expression recognition in video. Firstly, OpenFace 2.0 is used to detect face images in video, and two deep convolution neural networks are used to extract spatiotemporal expression features. Furthermore, spatial convolution neural network is used to extract the spatial information features of each static expression image, and the dynamic information feature is extracted from the optical flow information of multiple expression images based on temporal convolution neural network. Then, the spatiotemporal features learned by the two deep convolution neural networks are fused by multiplication. Finally, the fused features are input into support vector machine to realize the facial expression classification. Experimental results show that the recognition accuracy of the proposed method can reach 64.57% and 60.89%, respectively on RML and Baum-ls datasets. It is better than that of other contrast methods.

• 한국정보시스템학회지:정보시스템연구
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• 제32권2호
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• pp.87-108
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• 2023

Purpose The main purpose of this study is to improve fake news detection performance by using video information to overcome the limitations of extant text- and image-oriented studies that do not reflect the latest news consumption trend. Design/methodology/approach This study collected video clips and related information including news scripts, speakers' facial expression, and video metadata from YouTube to develop fake news detection model. Based on the collected data, seven combinations of related information (i.e. scripts, video metadata, facial expression, scripts and video metadata, scripts and facial expression, and scripts, video metadata, and facial expression) were used as an input for taining and evaluation. The input data was analyzed using six models such as support vector machine and deep neural network. The area under the curve(AUC) was used to evaluate the performance of classification model. Findings The results showed that the ACU and accuracy values of three features combination (scripts, video metadata, and facial expression) were the highest in logistic regression, naïve bayes, and deep neural network models. This result implied that the fake news detection could be improved by using video information(video metadata and facial expression). Sample size of this study was relatively small. The generalizablity of the results would be enhanced with a larger sample size.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2012년도 추계학술대회
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• pp.881-886
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• 2012

The paper is facial expression recognition based on the inclined face geometrical information. In facial expression recognition, mouth has a key role in expressing emotions, in this paper the features is mainly based on the shapes of mouth, followed by eyes and eyebrows. This paper makes its efforts to disperse every feature values via the weighting function and proposes method of expression classification with excellent classification effects; the final recognition model has been constructed.

• Journal of Information Processing Systems
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• 제19권3호
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• pp.323-333
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• 2023

Facial expression recognition can aid in the development of fatigue driving detection, teaching quality evaluation, and other fields. In this study, a facial expression recognition method was proposed with a residual masking reconstruction network as its backbone to achieve more efficient expression recognition and classification. The residual layer was used to acquire and capture the information features of the input image, and the masking layer was used for the weight coefficients corresponding to different information features to achieve accurate and effective image analysis for images of different sizes. To further improve the performance of expression analysis, the loss function of the model is optimized from two aspects, feature dimension and data dimension, to enhance the accurate mapping relationship between facial features and emotional labels. The simulation results show that the ROC of the proposed method was maintained above 0.9995, which can accurately distinguish different expressions. The precision was 75.98%, indicating excellent performance of the facial expression recognition model.

• 한국실내디자인학회논문집
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• 제22권1호
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• pp.105-114
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• 2013

This study investigated the application and the change of various architectural models by analyzing expression viewpoint media, which were applied to the visual information of digitalized 3D contemporary architectural models. The purpose of this study was to specify how modern architects have changed 3D architectural models to conceptual, logical, and formational visual information in the process of design. This study discovered a framework of analyses by theoretically investigating a relationship between expression media and expression change in the process of visualizing architectural models. Using the framework of analyses, this study analyzed how the expression viewpoints of architectural model information have been changed and applied. The transformation media of the visual information of digitalized 3D architectural models can be classified into conceptual, analytical, and formational information: 1) Contemporary architects used author-centered subjective viewpoints to express architectural concepts, which were generated in the process of their design. They selected a perspective viewpoint and a bird's eye view in order to present their architectural concepts and to depict them with one architectural model by expanding the visual scope of conceptual information. 2) Contemporary architects adopted observer-centered objective bird's eye view expression media to effectively present their architectural information to building owners and viewers. They used transformal media, which integrate architectural information into 3D and change it to different scales, in order to express their architecture logically. 3) Contemporary architects delivered model information about the generation and change of forms by expressing the image of a project from an author-centered viewpoint, instead of objectively defining formational information. They explained the generation principle of architectural forms via transformal media which develop and rotate an architectural model.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2014년도 추계학술대회
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• pp.197-200
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• 2014

본 논문은 얼굴의 표정 인식을 이용한 위험상황 인지 알고리즘을 제안한다. 제안방법은 인간의 다양한 감정 표정 중 위험상황을 인지하기 위한 표정인 놀람과 공포의 표정을 인식한다. 제안방법은 먼저 얼굴 영역을 추출하고 검출된 얼굴 영역으로부터 눈 영역과 입술 영역을 추출한다. 각 영역에 Uniform LBP 방법을 적용하여 표정을 판별하고 위험 상황을 인식한다. 제안방법은 Cohn-Kanade 데이터베이스 영상을 대상으로 성능을 평가하였다. 그 결과 표정 인식에 좋은 결과를 보였으며 이를 이용하여 위험상황을 잘 판별하였다.

• Journal of the Korean Data and Information Science Society
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• 제25권5호
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• pp.1151-1160
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• 2014

In DNA microarray studies, the number of genes far exceeds the number of samples and the gene expression measures are highly correlated. Partial least squares regression (PLSR) is one of the popular methods for dimensional reduction and known to be useful for the classifications of microarray data by several studies. In this study, we suggest a modified version of the partial least squares regression to analyze gene expression data with survival information. The method is designed as a new gene selection method using PLSR with an iterative procedure of imputing censored survival time. Mean square error of prediction criterion is used to determine the dimension of the model. To visualize the data, plot for variables superimposed with samples are used. The method is applied to two microarray data sets, both containing survival time. The results show that the proposed method works well for interpreting gene expression microarray data.