• Journal of Korea Society of Industrial Information Systems
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• v.5 no.1
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• pp.25-30
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• 2000

Hangul is regarded as one of the difficult character set due to the large number of classes and the shape similarity among different characters. Most of the conventional researches attempted to recognize the 2,350 characters which are popularly used, but this approach has a problem or low recognition performance while it provides a generality. On the contrary, recognition of a small character set appearing in specific fields like postal address or bank checks is more practical approach. This paper describes a research for recognizing the handwritten Hangul characters appearing in monetary fields. The modular neural network is adopted for the classification and three kinds of feature are tested. The experiment performed using standard Hangul database PE92 showed the correct recognition rate 91.56%.

• Journal of Information Processing Systems
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• v.18 no.3
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• pp.411-427
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• 2022

Digging historical and cultural information from seals in ancient books is of great significance. However, ancient Chinese seal samples are scarce and carving methods are diverse, and traditional digital image processing methods based on greyscale have difficulty achieving superior segmentation and recognition performance. Recently, some deep learning algorithms have been proposed to address this problem; however, current neural networks are difficult to train owing to the lack of datasets. To solve the afore-mentioned problems, we proposed an SEL-RefineMask which combines selector of feature pyramid network (SEL-FPN) with RefineMask to segment and recognize seals. We designed an SEL-FPN to intelligently select a specific layer which represents different scales in the FPN and reduces the number of anchor frames. We performed experiments on some instance segmentation networks as the baseline method, and the top-1 segmentation result of 64.93% is 5.73% higher than that of humans. The top-1 result of the SEL-RefineMask network reached 67.96% which surpassed the baseline results. After segmentation, a vision transformer was used to recognize the segmentation output, and the accuracy reached 91%. Furthermore, a dataset of seals in ancient Chinese books (SACB) for segmentation and small seal font (SSF) for recognition were established which are publicly available on the website.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.748-750
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• 2023

Facial expression recognition technology's rapid growth and development have garnered significant attention in recent years. This technology holds immense potential for various applications, making it crucial to stay up-to-date with the latest trends and advancements. Simultaneously, it is essential to identify and address the challenges that impede the technology's progress. Motivated by these factors, this study aims to understand the latest trends, future directions, and challenges in facial expression recognition technology by utilizing text mining to analyze papers published between 2020 and 2023. Our research focuses on discerning which aspects of these papers provide valuable insights into the field's recent developments and issues. By doing so, we aim to present the information in an accessible and engaging manner for readers, enabling them to understand the current state and future potential of facial expression recognition technology. Ultimately, our study seeks to contribute to the ongoing dialogue and facilitate further advancements in this rapidly evolving field.

• Phonetics and Speech Sciences
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• v.15 no.3
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• pp.83-88
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• 2023

This study investigates the fine-tuning of large-scale Automatic Speech Recognition (ASR) models, specifically OpenAI's Whisper model, for domain-specific applications using the KsponSpeech dataset. The primary research questions address the effectiveness of targeted lexical item emphasis during fine-tuning, its impact on domain-specific performance, and whether the fine-tuned model can maintain generalization capabilities across different languages and environments. Experiments were conducted using two fine-tuning datasets: Set A, a small subset emphasizing specific lexical items, and Set B, consisting of the entire KsponSpeech dataset. Results showed that fine-tuning with targeted lexical items increased recognition accuracy and improved domain-specific performance, with generalization capabilities maintained when fine-tuned with a smaller dataset. For noisier environments, a trade-off between specificity and generalization capabilities was observed. This study highlights the potential of fine-tuning using minimal domain-specific data to achieve satisfactory results, emphasizing the importance of balancing specialization and generalization for ASR models. Future research could explore different fine-tuning strategies and novel technologies such as prompting to further enhance large-scale ASR models' domain-specific performance.

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.33-40
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• 2023

As South Korea enters the realm of an super-aging society, the demand for elderly welfare services has been steadily rising. However, the current shortage of welfare personnel has emerged as a social issue. To address this challenge, there is active research underway on elderly care robots designed to mitigate the social isolation of the elderly and provide emergency contact capabilities in critical situations. Nonetheless, these functionalities require direct user contact, which represents a limitation of conventional elderly care robots. In this paper, we propose a solution to overcome these challenges by introducing a care robot system capable of interacting with users without the need for direct physical contact. This system leverages commercialized elderly care robots and cameras. We have equipped the care robot with an edge device that incorporates facial expression recognition and action recognition models. The models were trained and validated using public available data. Experimental results demonstrate high accuracy rates, with facial expression recognition achieving 96.5% accuracy and action recognition reaching 90.9%. Furthermore, the inference times for these processes are 50ms and 350ms, respectively. These findings affirm that our proposed system offers efficient and accurate facial and action recognition, enabling seamless interaction even in non-contact situations.

• Proceedings of the IEEK Conference
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• 2000.11c
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• pp.145-148
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• 2000

This paper proposes a character segmentation method for Korean letter address image. The poor quality of image binarization results in broken character strokes. To overcome this problem, two steps of processing ate introduced. The first one is to merge broken characters to generate character candidates, and the other one is to reduce the complexity of segmentation graph path. These two steps do not use recognition information to keep in high-speed.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10b
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• pp.335-337
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• 2000

본 연구에서는 문자 인식의 응용으로서 인쇄된 우편봉투의 주소를 인식한다. 스캐너로 입력된 우편봉투 영상으로부터 주소영역과 우편번호 영역을 분리한다. 분리된 각각의 영역에서 문자를 추출하고, 전처리로써 정규화, 특징추출 단계를 거쳐 우편번호와 주소를 각각 인식하였다. 이때, 우편번호 인식에 의하여 알 수 있는 주소와 실제로 인식한 주소의 신뢰도를 계산하여, 주소 인식 결과를 보정하는 과정을 거쳐 우편봉투의 인식을 실행하였다.

• Journal of Embryo Transfer
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• v.16 no.1
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• pp.61-68
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• 2001

Sperm competent for fertilization can become capacitated, bind to the zona pellucida (ZP) of an egg in a specific manner, and complete acrosomal exocytosis. Failure to carry out these functions results in infertility. Although the interactions between the ZP and the plasma mem-brane overlying the sperm acrosome have been considered important for sperm-egg recognition and signalling, recent results have prompted a reassessment of current paradigms concerning these interactions. In this review, we're going to discuss about the roles of the acrosomal matrix, the particulate component of the acrosomal contents, in fertilization. The general hypothesis is that acrosomal exocytosis leads to the exposure of acrosomal matrix proteins that become de-facto extracellular matrix (ECM) on the surface of the sperm head, and that the dynamic interactions of this newly-exposed sperm ECM with the egg ECM (the ZP) govern sperm-egg recognition and sperm penetration of the ZP Informations from these experiments may provide new ways to address the poor ZP binding of sperm from some human infertility patients and may offer new avenues for contraception through the disruption of purposeful sperm-ZP binding.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.05a
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• pp.726-729
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• 2006

As a active soundscape facility, P.A. system is a useful instrument to give place identity and vitality by letting out music, environmental music, bird singing sound etc. In this study, to know the optimistic distance and sound level range of introducing sound, sound levels due to distance were measured and subject responses were checked by questionnaire. Levels from 64dB to 71dB are recommended by subjects. And the optimistic level of introducing level is related with level variance of sound source. The results of this study could used for street furniture location design and P.A. system output level.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.11a
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• pp.201-204
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• 1997

최근 주소를 자동으로 인식하여 우편물 분류와 같은 업무를 효과적으로 수행하기 위한 연구가 진행되고 있다. 기존 연구들은 낱자 단위의 인식을 수행한 후 사전 형태의 간단한 DB를 통해 최종의 결과를 생성한다. 그러나 한글과 같은 복잡한 구조의 필기 문자에 대한 인식기의 성능은 아직도 미흡한 상태이다. 따라서 낱자 인식기의 성능에 의존하는 현재와 같은 방법으로는 만족할 만한 결과를 얻기가 힘들 것으로 생각된다. 본 논문에서는 낱자 인식 결과에 크게 의존하지 않고 주소에 나타나는 단어의 낱자들 사이간 연결 정보를 이용하여 단어를 인식할 수 있는 시스템을 제안한다. 본 시스템은 통계적 인식기를 사용하여 낱자를 인식하는 부분과 낱자 인식 결과를 조합하여 단어 수준의 인식과정을 통해 최종의 결과를 생성하는 부분으로 구성된다. 통계적 인식기는 Nearest neighborhood 방법을 사용하여 간단한 형태로 구현하였다. 단어인식 모듈은 단어에서 모든 문자간의 관계를 표현할 수 있도록 HMM 모형을 사용하여 어휘정보 네트워크를 구성하고 이를 이용하여 주소에 나타나는 단어를 인식하도록 하였다. PE92 한글 문자 데이터를 이용하여 실험을 수 璿\ulcorner 결과, 통계적 인식기의 성능이 저조함에도 불구하고 HMM을 이용한 어휘정보 네트워크가 이를 보완함으로써 좋은 결과를 얻었다. 이러한 단어 인식 방법을 주소 이외의 다른 단어 집합에 대해서도 쉽게 적용될 수 있을 것으로 예상된다.