• 한국음향학회:학술대회논문집
• /
• 한국음향학회 1995년도 제12회 음성통신 및 신호처리 워크샵 논문집 (SCAS 12권 1호)
• /
• pp.69-72
• /
• 1995

In this paper, a new approach for Korean connected digits recognition using the spatio-temporal neural network is reported. The data of seven digits phone numbers are used in the recognition of connected words, and in the initial experiment, digit recognition rate of 28% was achieved. In this paper, to increase recognition rate, two different approaches are analyzed. In the first system, to compensate the STNN's own defect and to emphasize the Korean word's phonic characters, the starting point of phone is pointed by comparing the average magnitude and zero-crossing rate and the ending point is pointed by comparing only zero-crossing rate. The digit recoginiton rate increased to 61%. Also, in the second system, to consider fact that same word's phone is varied severally, the number of STNN's of each word is increased from one to five, and then the varied same word's phones can be included to the increased STNN's. The digit recogniton rate of connected words increased to 89%.

• 통상정보연구
• /
• 제10권4호
• /
• pp.203-219
• /
• 2008

This study shows the following results. First, the assessment items of the whole exhibition operation, workforce, counselor's ability, facility and environment were important analysis factors for exhibition recognition, quality of human operation and quality of exhibition facility and environment. Second, exhibition recognition was found to be the most significant factor that influenced exhibitor's cognitive achievement, exhibition employee operation and exhibition facility. Third, exhibitors' satisfaction simultaneously increased as exhibition recognition and employee operation quality were raised. However, exhibition facility didn't strongly influence exhibitors' satisfaction. Fourth, high exhibition recognition, employee operation and exhibition facility resulted in high cognitive achievement and exhibitor's loyalty. Fifth, exhibition recognition is a highly influential factor to mediate exhibitor's cognitive achievement and exhibitors' loyalty. It implied that exhibitors' cognitive achievement and satisfaction were significantly related to the exhibition quality factor. Moreover, it indicated the effective and efficient operational method to strengthen promotional strategy, enhance the quality of employee operation, exhibition facility and environment. Thus, the results suggest a new method to evaluate exhibitor's satisfaction in the exhibition industry.

• 한국정보과학회:학술대회논문집
• /
• 한국정보과학회 2007년도 가을 학술발표논문집 Vol.34 No.2 (C)
• /
• pp.263-266
• /
• 2007

We introduce a vision-based hand gesture recognition fer understanding musical time and patterns without extra special devices. We suggest a simple and reliable vision-based hand gesture recognition having two features First, the motion-direction code is proposed, which is a quantized code for motion directions. Second, the conducting feature point (CFP) where the point of sudden motion changes is also proposed. The proposed hand gesture recognition system extracts the human hand region by segmenting the depth information generated by stereo matching of image sequences. And then, it follows the motion of the center of the gravity(COG) of the extracted hand region and generates the gesture features such as CFP and the direction-code finally, we obtain the current timing pattern of beat and tempo of the playing music. The experimental results on the test data set show that the musical time pattern and tempo recognition rate is over 86.42% for the motion histogram matching, and 79.75% fer the CFP tracking only.

• 전자공학회논문지B
• /
• 제30B권6호
• /
• pp.76-85
• /
• 1993

In this paper, we propose a stroke matching method for the off-line recognition of handprinted Hangul. In this method, the preprocessing steps such as position normalization, contour tracing and thinning are carried out first. Then, after extracting features such as the firection component distribution of contour, the direction component distribution of skeleton, and the distribution of structural feature points, strokes are extracted and matched based on the midpont distribution of the direction and the length of each stroke. In order to reduce the recognition time, a preliminary classification based on the direction component distribution features of the contour is performed. In order to domonstrate the performance of the proposed method, experiments with 520 most frequently used Hangul were performed, and 90.7% of correct recognition rate and 0.46second of recognition time per one character has been obtained. This results reveal that the proposed method can absorb effectively the noise in input character and the variations of stroke slant.

• ETRI Journal
• /
• 제40권6호
• /
• pp.774-787
• /
• 2018

Arabic handwriting segmentation and recognition is an area of research that has not yet been fully understood. Dealing with Arabic ligature segmentation, where the Arabic characters are connected and unconstrained naturally, is one of the fundamental problems when dealing with the Arabic script. Arabic character-recognition techniques consider ligatures as new classes in addition to the classes of the Arabic characters. This paper introduces an enhanced technique for Arabic handwriting recognition using the deep belief network (DBN) and a new morphological algorithm for ligature segmentation. There are two main stages for the implementation of this technique. The first stage involves an enhanced technique of the Sari segmentation algorithm, where a new ligature segmentation algorithm is developed. The second stage involves the Arabic character recognition using DBNs and support vector machines (SVMs). The two stages are tested on the IFN/ENIT and HACDB databases, and the results obtained proved the effectiveness of the proposed algorithm compared with other existing systems.

• 한국응급구조학회지
• /
• 제25권2호
• /
• pp.55-69
• /
• 2021

Purpose: This study aimed to develop 360° virtual reality videos and common videos for cardiac arrest recognition. Methods: A sequential mixed methods study was conducted, using qualitative interviews (with a total of seven experts) and a quantitative survey. Results: First, the cardiac arrest situation should be developed within 2-3 minutes after witnessing the patient collapse, for each of the four cardiac arrest videos about apnea, gasping, seizure, gasping, and seizure. Second, the education program should be designed so that the education on cardiac arrest recognition can proceed before CPR practice begins. Conclusion: 360° virtual reality videos and common videos for cardiac arrest recognition can play an important role in the education of the general public about cardiac arrest experience.

• 자동차안전학회지
• /
• 제14권4호
• /
• pp.6-15
• /
• 2022

In this study, a traffic light recognition algorithm was implemented and validated for low-speed special purpose vehicles in an urban environment. Real-time image data using a camera and YOLO algorithm were applied. Two methods were presented to increase the accuracy of the traffic light recognition algorithm, and it was confirmed that the second method had the higher accuracy according to the traffic light type. In addition, it was confirmed that the optimal YOLO algorithm was YOLO v5m, which has over 98% mAP values and higher efficiency. In the future, it is thought that the traffic light recognition algorithm can be used as a dual system to secure the platform safety in the traffic information error of C-ITS.

• Journal of Information Processing Systems
• /
• 제18권4호
• /
• pp.480-488
• /
• 2022

Images of tobacco retail licenses have complex unstructured characteristics, which is an urgent technical problem in the robot process automation of tobacco marketing. In this paper, a novel recognition approach using a double attention mechanism is presented to realize the automatic recognition and information extraction from such images. First, we utilized a DenseNet network to extract the license information from the input tobacco retail license data. Second, bi-directional long short-term memory was used for coding and decoding using a continuous decoder integrating dual attention to realize the recognition and information extraction of tobacco retail license images without segmentation. Finally, several performance experiments were conducted using a largescale dataset of tobacco retail licenses. The experimental results show that the proposed approach achieves a correction accuracy of 98.36% on the ZY-LQ dataset, outperforming most existing methods.

• Journal of Information Processing Systems
• /
• 제18권3호
• /
• pp.311-318
• /
• 2022

Tobacco sales enterprises often need to summarize and verify the daily sales bills, which may consume substantial manpower, and manual verification is prone to occasional errors. The use of artificial intelligence technology to realize the automatic identification and verification of such bills offers important practical significance. This study presents a novel multi-branch residual network for tobacco sales bills to improve the efficiency and accuracy of tobacco sales. First, geometric correction and edge alignment were performed on the input sales bill image. Second, the multi-branch residual network recognition model is established and trained using the preprocessed data. The comparative experimental results demonstrated that the correct recognition rate of the proposed method reached 98.84% on the China Tobacco Bill Image dataset, which is superior to that of most existing recognition methods.

• Steel and Composite Structures
• /
• 제21권6호
• /
• pp.1183-1210
• /
• 2016

Viscoelastic sandwich structures (VSSs) are widely used in mechanical equipment, but in the service process, they always suffer from aging which affect the whole performance of equipment. Therefore, aging state recognition of VSSs is significant to monitor structural state and ensure the reliability of equipment. However, non-stationary vibration response signals and weak state change characteristics make this task challenging. This paper proposes a novel method for this task based on adaptive second generation wavelet packet transform (ASGWPT) and multiwavelet support vector machine (MWSVM). For obtaining sensitive feature parameters to different structural aging states, the ASGWPT, its wavelet function can adaptively match the frequency spectrum characteristics of inspected vibration response signal, is developed to process the vibration response signals for energy feature extraction. With the aim to improve the classification performance of SVM, based on the kernel method of SVM and multiwavelet theory, multiwavelet kernel functions are constructed, and then MWSVM is developed to classify the different aging states. In order to demonstrate the effectiveness of the proposed method, different aging states of a VSS are created through the hot oxygen accelerated aging of viscoelastic material. The application results show that the proposed method can accurately and automatically recognize the different structural aging states and act as a promising approach to aging state recognition of VSSs. Furthermore, the capability of ASGWPT in processing the vibration response signals for feature extraction is validated by the comparisons with conventional second generation wavelet packet transform, and the performance of MWSVM in classifying the structural aging states is validated by the comparisons with traditional wavelet support vector machine.