• Journal of Digital Contents Society
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• 제18권1호
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• pp.231-238
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• 2017

Today, as a means of online communication, the use of emoticons is activated in SNS. Emoticon is an important element to share impact effects and fun together with various content design attempts. In this paper, we analyze the expression patterns changed through development process of emoticons, and analyze characteristics and effects of emoticons which are combined with traditional culture among the types of emoticons currently used.

• The Journal of Korean Institute of Communications and Information Sciences
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• 제21권12호
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• pp.3265-3276
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• 1996

The studies of document recongnition have been focused mainly on Korean documents. But most of documents composed of Korean and other characters. So, in this paper, we propose the document recognition system that can recognize the multi-size, multi font and mixed type characters. We have utilized a large scale network model, "CombNET" which consists of a 4 layered network with combstructure. And we propose recognition method that can recognize characters without discrimination of character type. The first layer constitutes a Kohonen's SOFM network which quantizes an input feature vector space into several sub-spaces and the following 2-4 layers constitutes BP network modules which classify input data in each sub-space into specified catagories. An experimental result demonstrated the usefulness of this approach with the recognition rates of 95.6% for the training data. For the mixed type character documents we obtained the recognition rates of 92.6% and recognition speed of 10.3 characters per second.

• IEMEK Journal of Embedded Systems and Applications
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• 제15권2호
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• pp.51-60
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• 2020

Optical character recognition (OCR) has been studied for decades because it is very useful in a variety of places. Nowadays, OCR's performance has improved significantly due to outstanding deep learning technology. Thus, there is an increasing demand for commercial-grade but affordable OCR systems. We have developed a low-cost, high-performance OCR system for the industry with the cheapest embedded developer kit that supports GPU acceleration. To achieve high accuracy for industrial use on limited computing resources, we chose a state-of-the-art text recognition algorithm that uses an end-to-end deep learning network as a baseline model. The model was then improved by replacing the feature extraction network with the best one suited to our conditions. Among the various candidate networks, EfficientNet-B3 has shown the best performance: excellent recognition accuracy with relatively low memory consumption. Besides, we have optimized the model written in TensorFlow's Python API using TensorFlow-TensorRT integration and TensorFlow's C++ API, respectively.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 한국퍼지및지능시스템학회 2004년도 춘계학술대회 학술발표 논문집 제14권 제1호
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• pp.491-494
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• 2004

Neural Oscillator can be applied to oscillatory systems such as the image recognition, the voice recognition, estimate of the weather fluctuation and analysis of geological fluctuation etc in nature and principally, it is used often to pattern recoglition of image information. Conventional BPL(Back-Propagation Learning) and MLNN(Multi Layer Neural Network) are not proper for oscillatory systems because these algorithm complicate Learning structure, have tedious procedures and sluggish convergence problem. However, these problems can be easily solved by using a synchrony characteristic of neural oscillator with PLL(phase-Locked Loop) function and by using a simple Hebbian learning rule. And also, Recognition velocity of Korean Character can be improved by using a Neural Oscillator's learning accelerator factor η$\_$ij/

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국제학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.76-80
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• 1993

In this paper we discuss optimization of neural network parameters, such as inclination of the sigmoid function, the numbers of the input layer's units and the hidden layer's units, considering application to recognition of hand written Hangul. Hangul characters are composed of vowels and consonants, and basically classified to six patterns by their positions. Using these characteristics of Hangul, the pattern of a given character is determined by its peripheral distribution and the other features. After then, the vowels and the consonants are recognized by the optimized neural network. The constructed recognition system including a neural network is applied to non-learning Hangul written by some Korean people, which are the names randomly taken from Korean spiritual and cultural research institute.

• Korea Science and Art Forum
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• 제37권3호
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• pp.125-134
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• 2019

This study was conducted to organize a program to classify and analyze the characteristics of images for the automation of background music selection in the video content production process. The results and contents of the study are as follows: video characteristics are selected as subject category, emotion, pixel motion speed, color, and character material. Subject categories and feelings were extracted using Microsoft's Azure Video Indexer, Pixel Movement Speed was an Optional flow, Color was an Image Histogram for Image, and character materials was CNN(Convolutional Neural Network). The results of this study are significant in that video analysis was conducted to match background music in the recent content production process of 'Internet One-person Broadcasting Creators'.

• Journal of the Korean Regional Science Association
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• 제15권2호
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• pp.5-19
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• 1999

This paper identifies five factors that limited urban network formation in Northeast Asia over the past half millennium, questions the extent to which they are being overcome in the 1990s, and sketches a network of cities that could boost regionalism. It briefly traces the historical evolution of these factors, including comparisons with European integration, while focusing primarily on the policies of the 1990s that have affected their continuing role. First is the factor of closed national markets with weak regional integration. Second is the preeminence of administrative means of integration over commercial ones. Third is the character of localism, shackled by overcentralization and weak cross-border linkages. Fourth is the limited nature of internationalism, dominated by state catch-up policies with one-sided global involvement. Fifth is a lack of regional consciousness. Just as national urban integration was essential for regional networks to form, without regional integration it is difficult to contemplate Northeast Asian cities taking their rightful place in a global urban network. After noting the failures of the 1990s, the paper points to the potential role as dragon's heads for sub-regional urban networks of potential front-line cities: Tumen, Sapporo, Irkutsk, and what I call the Amur triangle. Also of interest are how the capitals of Beijing, Moscow, Seoul, and Tokyo will adjust to a transformed urban network. After all, their current skepticism must be overcome with a program that links the benefits on all sides in order to build trust in regionalism. This requires internationalism and symbols of a balanced approach to each country's needs.

• Journal of the Korean Institute of Telematics and Electronics T
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• 제35T권3호
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• pp.46-52
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• 1998

In this paper, after inputting the computer with the attached number plate on the vehicle, using it, the color decomposition method and back propagation neural network proposed the extractable method of the vehicle number plate at high speed. This method separated R, G, B signal form input moving vehicle image to computer through video camera, then after transform this R, G, B signal into input image data of the computer by using color depth of vehicle number plate and store up binary value in the memory frame buffer. After adapting character's recognition algorithm, also improving this, by adapting back propagation neural network makes the vehicle number plate recognition system. Also minimalizing the similar color's confusion, adapting horizontal and vertical extracting algorithm by using the vehicle's rectangular architecture shows the extract and character's recognition of the vehicle number plate at high speed.

• The Journal of the Korea institute of electronic communication sciences
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• 제13권3호
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• pp.643-650
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• 2018

This service uses beacon with BLE technology, and USER APP has priority with Anchor IPS which secures location and device. Since then, it has been linked with character beacons that can be used in various places. The character beacon which is recognized as a service is able to confirm the user's location through API key of the LBS CMS server, and receives various contents services of the UESR CMS server. The service network consists of character beacon, Anchor IPS, USER APP, LBS CMS server, and USER CMS server. The purpose of the service is to promote local tourism and local culture to tourists through local unique characters.

• Journal of the Korea Computer Graphics Society
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• 제26권4호
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• pp.1-8
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• 2020

Motion synthesis using physics-based controllers can generate a character animation that interacts naturally with the given environment and other characters. Recently, various methods using deep neural networks have improved the quality of motions generated by physics-based controllers. In this paper, we present a control policy learned by deep reinforcement learning (DRL) that enables Luxo, the mascot character of Pixar animation studio, to run towards a random goal location while imitating a reference motion and maintaining its balance. Instead of directly training our DRL network to make Luxo reach a goal location, we use a reference motion that is generated to keep Luxo animation's jumping style. The reference motion is generated by linearly interpolating predetermined poses, which are defined with Luxo character's each joint angle. By applying our method, we could confirm a better Luxo policy compared to the one without any reference motions.