• 제목/요약/키워드: Type Recognition

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가상 데이터를 활용한 번호판 문자 인식 및 차종 인식 시스템 제안 (Proposal for License Plate Recognition Using Synthetic Data and Vehicle Type Recognition System)

  • 이승주;박구만
    • 방송공학회논문지
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    • 제25권5호
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    • pp.776-788
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    • 2020
  • 본 논문에서는 딥러닝을 이용한 차종 인식과 자동차 번호판 문자 인식 시스템을 제안한다. 기존 시스템에서는 영상처리를 통한 번호판 영역 추출과 DNN을 이용한 문자 인식 방법을 사용하였다. 이러한 시스템은 환경이 변화되면 인식률이 하락되는 문제가 있다. 따라서, 제안하는 시스템은 실시간 검출과 환경 변화에 따른 정확도 하락에 초점을 맞춰 1-stage 객체 검출 방법인 YOLO v3를 사용하였으며, RGB 카메라 한 대로 실시간 차종 및 번호판 문자 인식이 가능하다. 학습데이터는 차종 인식과 자동차 번호판 영역 검출의 경우 실제 데이터를 사용하며, 자동차 번호판 문자 인식의 경우 가상 데이터만을 사용하였다. 각 모듈별 정확도는 차종 검출은 96.39%, 번호판 검출은 99.94%, 번호판 검출은 79.06%를 기록하였다. 이외에도 YOLO v3의 경량화 네트워크인 YOLO v3 tiny를 이용하여 정확도를 측정하였다.

욕구인식과 인지적 노력에 근거한 의류상품 비계획구매 의사결정과정 (The Decision Making Process of Unplanned Purchases of Clothing Based on Need Recognition and Cognitive Efforts)

  • 진현정;이은영
    • 한국의류학회지
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    • 제33권10호
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    • pp.1601-1610
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    • 2009
  • Unplanned purchase is an unexpected buying behavior affected by product or marketing stimuli. Unplanned purchase does not follow the order of the rational decision making process. Through an in-depth interview, this study classified the types of unplanned purchase of clothing and examined the decision-making processes. The results (according to the need recognition level of consumers prior to stimuli) show three types of unplanned purchase of clothing products that are classified as: the need-manifesting type, the need-embodying type, and the need-reminding type. In addition, each type is reclassified into the high-cognition type and the low-cognition type according to the cognitive effort level of consumers during the purchase decision-making process. The need-manifesting type recognized a buying need after exposure to stimuli and then engaged in unplanned purchases. The need-embodying type recognized a problem, but the purchase intention was not concrete. The need-reminding type recognized a desire to buy clothing products, but temporarily forgot it, and then later remembered the problem recognition from the past after experiencing the stimuli.

Q방법론을 활용한 중등예비체육교사의 육상운동에 대한 인식 연구 (Analysis on the Secondary Pre-Physical Education Teacher's Recognition for the Learning Athletics Using the Q Methodology)

  • 유영설
    • 한국융합학회논문지
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    • 제11권4호
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    • pp.311-321
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    • 2020
  • 본 연구는 육상운동에 대한 중등예비체육교사의 주관성을 탐색하는데 목적이 있다. 연구대상은 D시의 사범대학 체육교육과 2학년 학부생과 교육대학원생으로 총 28명으로 하였다. 연구방법은 인간의 주관적 인식을 탐색할 수 있는 Q방법론을 활용하였다. Q연구 과정을 통해 얻은 자료는 QUANL 프로그램을 통해 Q요인분석을 실시하여 총 4개의 유형으로 분류되었다. 제1유형은, 육상운동은 성취감을 느끼게 해 주고 리듬감이 중요하며 도전의식의 가치를 강조하여 '교육적 가치 인식형'으로 명명하였다. 제2유형은, 육상운동은 체력향상을 위한 트레이닝과 재미있는 보조운동의 필요성을 강조하여 '보조 활동 중요성 인식형'으로 명명하였다. 제3유형은, 육상운동은 복잡한 동작 구성에 따른 기능 습득의 어려움과 높은 집중력의 요구 그리고 경험 부족을 강조하여 '기능 습득 곤란 인식형'으로 명명하였다. 제4유형은, 육상운동은 모든 활동과 운동의 기초이고 도전의식을 갖게 하며 모든 건강체력요소를 포함하는 운동이라는 점을 강조하여 '기초 운동 가치 인식형'으로 명명하였다.

Vehicle Image Recognition Using Deep Convolution Neural Network and Compressed Dictionary Learning

  • Zhou, Yanyan
    • Journal of Information Processing Systems
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    • 제17권2호
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    • pp.411-425
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    • 2021
  • In this paper, a vehicle recognition algorithm based on deep convolutional neural network and compression dictionary is proposed. Firstly, the network structure of fine vehicle recognition based on convolutional neural network is introduced. Then, a vehicle recognition system based on multi-scale pyramid convolutional neural network is constructed. The contribution of different networks to the recognition results is adjusted by the adaptive fusion method that adjusts the network according to the recognition accuracy of a single network. The proportion of output in the network output of the entire multiscale network. Then, the compressed dictionary learning and the data dimension reduction are carried out using the effective block structure method combined with very sparse random projection matrix, which solves the computational complexity caused by high-dimensional features and shortens the dictionary learning time. Finally, the sparse representation classification method is used to realize vehicle type recognition. The experimental results show that the detection effect of the proposed algorithm is stable in sunny, cloudy and rainy weather, and it has strong adaptability to typical application scenarios such as occlusion and blurring, with an average recognition rate of more than 95%.

문자형식 분류 기반의 인쇄체 문자인식에 관한 연구 (A Study on Machine Printed Character Recognition Based on Character Type Classification)

  • 임길택;김호연
    • 전자공학회논문지CI
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    • 제40권5호
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    • pp.266-279
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    • 2003
  • 본 논문에서는 문자의 형식정보를 이용하여 인식대상 문자군을 분할하여 인쇄체 문자를 인식하는 방법을 제안한다. 인식대상 문자를 전체 7개의 형식으로 나누는데, 한글 문자의 경우 자소 조합 방식에 따라 6개의 형식으로 분류하며, 영·숫자 및 기호 문자의 경우 1개의 형식으로 분류한다. 각 문자형식에 따라 입력 문자 영상을 몇 개의 인식단위로 나누고, 이에 대한 방향각도 특징을 추출하여 신경망 인식기에 입력하여 인식한 후 인식된 각 인식단위를 조합하여 문자인식을 한다. 각각 구현된 7가지 형식별 문자인식기를 단순 스위칭 및 통합 방법과 두 방법의 변형 방법 등 7가지의 방법으로 결합하여 최종 문자인식을 하였다. 실험 결과, 단순 스위칭 방법은 98.62%, 단순 통합 방법은 90.54%, 나머지 5가지의 변형 방법들이 97.35%에서 98.65%의 인식 성능을 보였다.

플라스틱 아이콘 형상의 손가락 촉지각률 향상을 위한 설계 가이드 (Design guides for enhancing finger tactile recognition of plastic icon shapes)

  • 김헌;이원영
    • Design & Manufacturing
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    • 제6권2호
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    • pp.59-63
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    • 2012
  • In various industries, tactile recognition has been one of the important ways in displaying information because peoples like to touch and feel. Especially, how much the tactile information is efficiently recognizable is crucial for visually impaired persons in their daily lifes. However, existing design guidelines are insufficient to lead good tactile recognition. In this study, an experiment was performed to investigate proper tactile shapes (relievo / intaglio vs. filled / unfilled), sizes and depths for efficient tactile recognition. Moreover, this study scrutinized whether the recognition speed or error was varied depending on the type of displayed symbols (open vs. closed types) in tactile. The experimental results revealed that the 'relieve-filled' shape type was more rapidly recognizable than the other shapes, and the 'closed' type symbols (e.g., ${\square }$. ${\bigcirc}$) were more robustly recognizable than the 'open' type symbols (e.g, +, ^). Several design guidelines were presented based on the results. These guidelines can be applied to the design of tactile buttons in the devices that users should control them without visual attention, such as car steering wheels or MP3 players.

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에지영상의 비율을 이용한 차종 인식 보안 알고리즘 (Security Algorithm for Vehicle Type Recognition)

  • 이유진
    • 융합정보논문지
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    • 제7권2호
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    • pp.77-82
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    • 2017
  • 본 논문은 차량영상을 입력영상으로 받아 차량의 종류를 인식하는 보안 알고리즘을 연구한다. 차량 인식 보안 알고리즘은 영상입력, 배경제거, 에지영역 추출, 전처리(이진화), 차량인식 등의 5가지 핵심부분으로 구성된다. 그러므로 차량 종류 인식 보안 알고리즘의 최종 인식율은 각 단계의 역할 및 기능에 직간접적인 영향을 받는다. 영상을 그레이 스케일 이미지로 입력시킨 후 배경을 제거하고, 에지영역만 추출한 후 이진화를 거친다. 외곽선을 또렷하게 해주기 위한 전처리 과정을 거친 후 차량의 높이와 넓이의 비율을 통해 차량의 종류를 대형차, 승용차, 오토바이의 3가지 범주로 나누게 했다.

중소규모 사업장의 교육 환경과 고용형태에 따른 호흡보호구 인식도 및 밀착계수 비교 (Comparison of Recognition and Fit Factors according to Education Actual Condition and Employment Type of Small and Medium Enterprises)

  • 어원석;최영보;신창섭
    • 한국안전학회지
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    • 제33권6호
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    • pp.28-36
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    • 2018
  • There was a difference in recognition of respirators according to the educational performance environment. they were showed higher recognition of respirators of group by internal and external mix trainer, less than 6 months, over 1hour, more than 5 times, variety of education. To identify the relationship between types of job classification(typical and atypical)and the levels of recognition of respirators, a total of 153 workers in a business workplace. mainly, typical workers showed higher recognition of respirators than atypical workers. Training of correct wearing showed high demands both typical and atypical workers. Descriptive statistics(SAS ver 9.2)was performed. the results of recognition of respirators were analyzed the mean and standard deviation by t-test, and anova, fit factor is used geometric means(geometric standard deviation), paired t-test, Wilcoxon analysis(P=0.05). Particulate filtering facepiece respirators (PFFR) is one of the most widely used items of personal protective equipments, and a tight fit of the respirators on the wearers is critical for the protection effectiveness. In order to effectively protect the workers through the respirators, it is important to find and evaluate the ways that can be readily applicable at the workplace to improve the fit of the respirators. This study was designed to evaluate effects of mask style (cup or foldable type) and donning training on fit factors (FF) of the respirators, since these are available at various workplace, especially at small business workplace. A total of 40 study subjects, comprised of employment type workers in metalworking industries, were enrolled in this study. The FF were quantitatively measured before and after training related to the proper donning and use of cup or foldable-type respirators. The pass/fail criterion of FF was set at 100. After the donning training for the cup-type mask, fit test were increased by 769%. but foldable-type mask was also increased after the donning training, the GM of FF for the foldable-type mask and it's increase rate were smaller as compared to the cup-type mask. Furthermore, the differences of the increase rates of the GM of FF in employment type of the subjects were not significantly for the foldable-type mask. These results imply that the raining on the donning and use of PFFR can enhance the protection effectiveness of cup or foldable-type mask, and that the training effects for the foldable-type mask is less significant than that for the cup-type mask. Therefore, it is recommended that the donning training and fit tests should be conducted before the use of the PFFR, and listening to workers opinion regularly.

도로영상에서 차량 특성 곡선을 이용한 차종 구분 알고리즘 개발

  • 김희식;이호재;이평원
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 1995년도 추계학술대회 논문집
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    • pp.423-426
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    • 1995
  • An image processing algorithm is developed in order to recognize the type of cars, the position of a number plate and the characters on the plate. To recognize the type af cars, comparison of two images is used. One has a car image, the other is just a background image without car. After that recognition, a vertical line filter is used to find the location of the plate. Finally the similarity method is used to recognize the numbers on the plates.

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머리 움직임 인식을 위한 근전도 신호의 패턴 인식 기법에 관한 연구 (A Study on the Pattern Recognition of EMG Signals for Head Motion Recognition)

  • 이태우;전창익;이영석;유세근;김성환
    • 대한전기학회논문지:시스템및제어부문D
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    • 제53권2호
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    • pp.103-110
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    • 2004
  • This paper proposes a new method on the EMG AR(autoregressive) modeling in pattern recognition for various head motions. The proper electrode placement in applying AR or cepstral coefficients for EMG signature discrimination is investigated. EMG signals are measured for different 10 motions with two electrode arrangements simultaneously. Electrode pairs are located separately on dominant muscles(S-type arrangement), because the bandwidth of signals obtained from S-type placement is wider than that from C-type(closely in the region between muscles). From the result of EMG pattern recognition test, the proposed mIAR(modified integrated mean autoregressive model) technique improves the recognitions rate around 17-21% compared with other the AR and cepstral methods.