• The Journal of Asian Finance, Economics and Business
• /
• v.7 no.11
• /
• pp.955-966
• /
• 2020

The purpose of this study is to find out how SNS marketing activities affect brand recognition, brand familiarity, and purchase intention for consumers who have purchased products from franchise chicken stores, including whether there is a moderating effect according to gender. SNS marketing activities were set up by configuring three attributes which are, SNS advertising, SNS information, and SNS events as sub-factors. For empirical analysis, a survey was conducted on SNS users, and SPSS/AMOS statistical programs were employed for the data analysis. First, the result of the empirical analysis showed that SNS advertising, SNS information, and SNS events have a significant positive effect on brand recognition. Second, it was found that the SNS events had a significant positive effect on brand familiarity. Third, it was found that SNS advertising has a significant positive effect on purchase intention. Fourth, it was observed that brand recognition has a significant positive effect on brand familiarity. Fifth, it was found that brand recognition and brand familiarity have a significant positive effect on purchase intention. Sixth, it was found that gender plays a significant role in the relationship between these constructs. Therefore, it can be assumed that the hypothesis presented in this study is sufficiently proven.

• ETRI Journal
• /
• v.37 no.6
• /
• pp.1220-1230
• /
• 2015

An autonomous valet parking (AVP) system is designed to locate a vacant parking space and park the vehicle in which it resides on behalf of the driver, once the driver has left the vehicle. In addition, the AVP is able to direct the vehicle to a location desired by the driver when requested. In this paper, for an AVP system, we introduce technology to recognize a parking space using image sensors. The proposed technology is mainly divided into three parts. First, spatial analysis is carried out using a height map that is based on dense motion stereo. Second, modelling of road markings is conducted using a probability map with a new salient-line feature extractor. Finally, parking space recognition is based on a Bayesian classifier. The experimental results show an execution time of up to 10 ms and a recognition rate of over 99%. Also, the performance and properties of the proposed technology were evaluated with a variety of data. Our algorithms, which are part of the proposed technology, are expected to apply to various research areas regarding autonomous vehicles, such as map generation, road marking recognition, localization, and environment recognition.

• International Journal of Computer Science & Network Security
• /
• v.22 no.11
• /
• pp.121-126
• /
• 2022

The number of vehicles has increased exponentially over the past 20 years due to technological advancements. It is becoming almost impossible to manually control and manage the traffic in a city like Karachi. Without license plate recognition, traffic management is impossible. The Framework for License Plate Detection & Recognition to overcome these issues is proposed. License Plate Detection & Recognition is primarily performed in two steps. The first step is to accurately detect the license plate in the given image, and the second step is to successfully read and recognize each character of that license plate. Some of the most common algorithms used in the past are based on colour, texture, edge-detection and template matching. Nowadays, many researchers are proposing methods based on deep learning. This research proposes a framework for License Plate Detection & Recognition using a custom YOLOv5 Object Detector, image segmentation techniques, and Tesseract's optical character recognition OCR. The accuracy of this framework is 0.89.

• MALSORI
• /
• no.57
• /
• pp.99-112
• /
• 2006

In this paper, we introduce two retrieval methods for photos with speech documents. We compare the pattern of speech query with those of speech documents recorded in digital cameras, and measure the similarities, and retrieve photos corresponding to the speech documents which have high similarity scores. As the first approach, a phoneme recognition scheme is used as the pre-processor for the pattern matching, and in the second one, the vector quantization (VQ) and the dynamic time warping (DTW) are applied to match the speech query with the documents in signal domain itself. Experimental results show that the performance of the first approach is highly dependent on that of phoneme recognition while the processing time is short. The second method provides a great improvement of performance. While the processing time is longer than that of the first method due to DTW, but we can reduce it by taking approximated methods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2009.10a
• /
• pp.173-174
• /
• 2009

Color harmony will look good formative elements of the basic lines, shapes and colors. In this paper, we present the implementation of Johannes Itten's color balance. Yellow, red, blue, on the basis of the first color mixing between the index and second color is placed. 12 color balance made by placing a third color between the first color and second color. we recognize this 12 color balance. Edge is detected using the Canny edge operator and labeling and clustering was expressed through the colors.

• Korean Journal of Applied Biomechanics
• /
• v.34 no.2
• /
• pp.71-80
• /
• 2024

Objective: This study aimed to explore the brain connectivity between brain and biomechanical variables by exploring motion recognition through FFT (fast fourier transform) analysis and AI (artificial intelligence) focusing on quiet standing movement patterns. Method: Participants included 12 young adult males, comprising university students (n=6) and elite gymnasts (n=6). The first experiment involved FFT of biomechanical signals (f_CoP, f_AJtorque and f_EEG), and the second experiment explored the optimization of AI-based GRU (gated recurrent unit) using f_EEG data. Results: Significant differences (p<.05) were observed in frequency bands and maximum power based on group and posture types in the first experiment. The second study improved motion prediction accuracy through GRU performance metrics derived from brain signals. Conclusion: This study delved into the movement pattern of upright standing posture through the analysis of bio-signals linking the cerebral cortex to motor performance, culminating in the attainment of motion recognition prediction performance.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.4 no.2
• /
• pp.149-154
• /
• 2004

In this research, we selected the speech recognition to implement the electric wheelchair system as a method to control it by only using the speech and used DTW (Dynamic Time Warping), which is speaker-dependent and has a relatively high recognition rate among the speech recognitions. However, it has to have small memory and fast process speed performance under consideration of real-time. Thus, we introduced VQ (Vector Quantization) which is widely used as a compression algorithm of speaker-independent recognition, to secure fast recognition and small memory. However, we found that the recognition rate decreased after using VQ. To improve the recognition rate, we applied ART2 (Adaptive Reason Theory 2) algorithm as a post-process algorithm to obtain about 5% recognition rate improvement. To utilize ART2, we have to apply an error range. In case that the subtraction of the first distance from the second distance for each distance obtained to apply DTW is 20 or more, the error range is applied. Likewise, ART2 was applied and we could obtain fast process and high recognition rate. Moreover, since this system is a moving object, the system should be implemented as an embedded one. Thus, we selected TMS320C32 chip, which can process significantly many calculations relatively fast, to implement the embedded system. Considering that the memory is speech, we used 128kbyte-RAM and 64kbyte ROM to save large amount of data. In case of speech input, we used 16-bit stereo audio codec, securing relatively accurate data through high resolution capacity.

• The Journal of the Korea Contents Association
• /
• v.19 no.8
• /
• pp.490-499
• /
• 2019

Face recognition payment service is an innovative payment method based on face recognition technology and is emerging in China now. Various industries regarding unmanned sales are likely to utilize this face recognition payment service in the future. This study investigated the factors influencing the usage intention of Chinese consumers who have experience using face recognition service. We used questionnaire survey and analysis with SPSS and AMOS. According to the results of the study, conclusions are as followed. First, consumers' attitudes toward the characteristic of face recognition payment service, which are non-contact and non-coercion, positively affected perceived usefulness. Second, the rapidness of the facial recognition payment among the recognition, the security and the rapidness of this service affected the ease of use. Third, social influences such as subjective norms also influence the intention to use. Fourth, the increase of the level of self-expression awareness and the intention of using face recognition payment service are confirmed. Through these results, the implications for design and communication of related innovative services were discussed.

• Journal of the Korean Society for Aviation and Aeronautics
• /
• v.31 no.3
• /
• pp.119-132
• /
• 2023

In recent years, the competition for employment among college students has become more intense. It is also the time when strong personal beliefs and will to develop careers are required for successful employment through stable major study. Therefore, in this study, we tried to find out the effect on major attitude and employment efficacy according to the level of aviation safety perception, which is an important issue in the aviation industry. For analysis, survey is conducted targeting college students majoring in aviation service who are enrolled in universities in the metropolitan area and Chungcheong area. To verify the hypotheses of the study, demographic characteristics are identified based on questionnaires, reliability and validity of measurement items are verified, and structural equation model analysis is performed to verify the hypotheses. The analysis results are as follows. First, it is found that safety knowledge and safety consciousness, which are sub-factors of aviation safety perception of college students majoring in aviation service, have a positive (+) effect on subject recognition, learning process recognition, and career recognition of major recognition. Second, subject recognition, learning process recognition, and career recognition, which are sub-factors of major recognition, are found to have a positive effect on major commitment. Third, it is found that major commitment have a positive (+) effect on employment efficacy. Based on the research results, practical support plans and strategies for effective major study and successful employment are presented.

• 제어로봇시스템학회:학술대회논문집
• /
• 2002.10a
• /
• pp.111.1-111
• /
• 2002

System configuration 1. First is the image acquisition part 2. Second part is for creating the vector image and for processing the obtained facial image. This part is for finding the facial area from the skin color. To do this, we can first find the skin color area with the highest weight from eigenface that consists of eigenvector. And then, we can create the vector image of eigenface from the obtained facial area. 3. Third is recognition module portion.