• Title/Summary/Keyword: recognition-rate

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Development of Interactive Signage using Floating Hologram (플로팅 홀로그램을 이용한 인터랙티브 사이니지 개발)

  • Kim, Dong-Jing;Jeong, Dong Hyo;Kim, Tae-Yong
    • Journal of the Institute of Convergence Signal Processing
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    • v.19 no.4
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    • pp.180-185
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    • 2018
  • We have developed an interactive signage system based on floating hologram by combining hologram technology and ICT technology, which can be competitive to small businesses that have excellent products and services. The developed interactive signage system can be used for publicity and marketing of small business owners at low cost, introducing menus with 3D hologram images, and providing various contents responding to user's hand movements. The developed system is able to detect 10 finger movements at a rate of 290 frames per second in a range of 60cm and a range of 150 degrees. We also confirmed that the virtual touch function operates normally by dividing the user's motion recognition into the hover zone and the touch zone by the physical motion experiment of the leap motion object.

A Study on H-CNN Based Pedestrian Detection Using LGP-FL and Hippocampal Structure (LGP-FL과 해마 구조를 이용한 H-CNN 기반 보행자 검출에 대한 연구)

  • Park, Su-Bin;Kang, Dae-Seong
    • The Journal of Korean Institute of Information Technology
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    • v.16 no.12
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    • pp.75-83
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    • 2018
  • Recently, autonomous vehicles have been actively studied. Pedestrian detection and recognition technology is important in autonomous vehicles. Pedestrian detection using CNN(Convolutional Neural Netwrok), which is mainly used recently, generally shows good performance, but there is a performance degradation depending on the environment of the image. In this paper, we propose a pedestrian detection system applying long-term memory structure of hippocampal neural network based on CNN network with LGP-FL (Local Gradient Pattern-Feature Layer) added. First, change the input image to a size of $227{\times}227$. Then, the feature is extracted through a total of 5 layers of convolution layer. In the process, LGP-FL adds the LGP feature pattern and stores the high-frequency pattern in the long-term memory. In the detection process, it is possible to detect the pedestrian more accurately by detecting using the LGP feature pattern information robust to brightness and color change. A comparison of the existing methods and the proposed method confirmed the increase of detection rate of about 1~4%.

A Study of Facial Organs Classification System Based on Fusion of CNN Features and Haar-CNN Features

  • Hao, Biao;Lim, Hye-Youn;Kang, Dae-Seong
    • The Journal of Korean Institute of Information Technology
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    • v.16 no.11
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    • pp.105-113
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    • 2018
  • In this paper, we proposed a method for effective classification of eye, nose, and mouth of human face. Most recent image classification uses Convolutional Neural Network(CNN). However, the features extracted by CNN are not sufficient and the classification effect is not too high. We proposed a new algorithm to improve the classification effect. The proposed method can be roughly divided into three parts. First, the Haar feature extraction algorithm is used to construct the eye, nose, and mouth dataset of face. The second, the model extracts CNN features of image using AlexNet. Finally, Haar-CNN features are extracted by performing convolution after Haar feature extraction. After that, CNN features and Haar-CNN features are fused and classify images using softmax. Recognition rate using mixed features could be increased about 4% than CNN feature. Experiments have demonstrated the performance of the proposed algorithm.

A Web-based Survey Research on Improving and Utilizing Korean Medicine Clinical Practice Guideline for Ankle Sprain (족관절 염좌 임상진료지침 개정과 활용도 향상을 위한 전자우편 설문조사)

  • Lee, Ji-Eun;Choi, Jin-Bong;Kim, Do-Hyeong;Jeong, Hyun-Jin;Kim, Jae-Hong
    • The Journal of Korean Medicine
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    • v.40 no.2
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    • pp.1-16
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    • 2019
  • Objectives: The purpose of this study was to increase the utilization of Korean Medicine Clinical Practice Guidelines(KMCGP) for ankle sprain by investigating the recognition of guideline developed in 2015 and evaluating the current status of treatment. Methods: An e - mail questionnaire survey was conducted for Korean medicine doctor(K.M.D) registered in Korean Medicine Association. Survey data were analyzed through Excel. Results: The most common Korean medicine treatments used in clinic were acupuncture(adjacent points)(28.5%), cupping therapy(19.7%) and pharmacopuncture(9.8%). The treatments with high patient satisfaction were acupuncture (adjacent points)(27.9%), moxibustion(22.4%) and herbal medicine(10.4%). Herbal medicine(17.9%), tuina(10.7%) and embedding therapy(9.2%) were difficult to perform during treatment because of cost. In the case of a later revision, respondents most thought it is necessary to update evidence and adjust recommendation ratings. A majority of all respondents said they would like to know about the revised guideline through the Internet. In the expected revision effect, the first order was 'presentation of standardized treatment method', the second was 'establishing the basis of Korean medicine treatment', and the third was 'strengthening the status of Korean medicine as therapeutic medicine'. Many respondents wished to add exercise therapy. In order to increase the utilization rate of the guideline, many respondents thought it should be included in textbooks and 90.6% of respondents answered that they would use more than 50% of the revised guideline. Conclusion: It is necessary to update evidence and adjust recommendation ratings and to promote KMCGP. At the same time treatment methods should be taught to K.M.D

Nomogram building to predict dyslipidemia using a naïve Bayesian classifier model (순수 베이지안 분류기 모델을 사용하여 이상지질혈증을 예측하는 노모 그램 구축)

  • Kim, Min-Ho;Seo, Ju-Hyun;Lee, Jea-Young
    • The Korean Journal of Applied Statistics
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    • v.32 no.4
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    • pp.619-630
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    • 2019
  • Dyslipidemia is a representative chronic disease affecting Koreans that requires continuous management. It is also a known risk factor for cardiovascular disease such as hypertension and diabetes. However, it is difficult to diagnose vascular disease without a medical examination. This study identifies risk factors for the recognition and prevention of dyslipidemia. By integrating them, we construct a statistical instrumental nomogram that can predict the incidence rate while visualizing. Data were from the Korean National Health and Nutrition Examination Survey (KNHANES) for 2013-2016. First, a chi-squared test identified twelve risk factors of dyslipidemia. We used a naïve Bayesian classifier model to construct a nomogram for the dyslipidemia. The constructed nomogram was verified using a receiver operating characteristics curve and calibration plot. Finally, we compared the logistic nomogram previously presented with the Bayesian nomogram proposed in this study.

The research of implementing safety driving system based on camera vision system (Camera Vision 기반 주행안전 시스템 구현에 관한 연구)

  • Park, Hwa-Beom;Kim, Young-Kil
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.23 no.9
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    • pp.1088-1095
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    • 2019
  • The information and communication technology that is being developed recently has been greatly influencing the automobile market. In recent years, devices equipped with IT technology have been installed for the safety and convenience of the driver. However, it has the advantage of increased convenience as well as the disadvantage of increasing traffic accidents due to driver's distraction. In order to prevent such accidents, it is necessary to develop safety systems of various types and ways. In this paper implements a platform that can recognize LDWS and FCWS and PDWS by using a single camera without using radar sensor and camera fusion and stereo camera method using two or more sensors, and proposes to study multi-function driving safety platform using a single camera by analyzing recognition rate evaluation and validity on a vehicle.

Development and Evaluation of Nutritional Education Program on Nutrition Labeling for Adults (성인 대상 영양표시 교육프로그램 개발 및 효과평가)

  • Kim, Mi-Hyun;Yeon, Jee-Young
    • Journal of the Korean Society of Food Culture
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    • v.34 no.1
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    • pp.34-43
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    • 2019
  • The aim of this study was to develop and evaluate a nutrition education program that was designed to increase the knowledge, attitudes, and skills of Korean adults regarding nutrition labeling. The education program was 45 minutes of short-term training, which was conducted in the form of lectures and exercises. The contents of the program were as follows: in the introduction stage, talking about status and reasons for checking nutrition labels; in the development stage, explanation of nutrition labeling and their content, reading, and identifying sample nutrition labels, as well as comparing nutrition labels and selecting better foods; in the closing stage, summary of nutrition labeling and a pledge to check nutrition labels when purchasing processed food. A total of 53 adults (88.5% female) aged 30 years and over participated in this study. The nutrition labeling awareness of the subjects was increased significantly from 55.8 to 96.2% after the education. After the education, the correct recognition rate of a nutrition label was increased significantly from 26.9 to 78.8% for the amount of food, from 25.0 to 73.1% for the calorie content, from 36.5 to 69.2% for the nutrient contents, and from 30.8 to 82.7% for the percent daily value. The self-efficacy of checking nutrition labels was also increased significantly compared to that before the education. The overall satisfaction score of the nutrition education program was 4.2 out of 5. The outcome showed that the nutrition education program of nutrition labeling improved the participants' awareness and self-efficacy towards checking nutrition labels.

Vascular Injuries Due to Penetrating Missile Trauma in Anti-Terrorism Ops

  • Dhillan, Rishi;Bhalla, Alok;Kumar Jha, Sushil;Singh, Hakam;Arora, Aman
    • Journal of Trauma and Injury
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    • v.32 no.2
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    • pp.93-100
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    • 2019
  • Purpose: Penetrating vascular trauma though less common poses a challenge to all Surgeons. This study was designed to analyse the profile, management modalities of vascular trauma and the outcomes thereof at a Trauma Care Centre in a Tertiary care setting in hostile environment in India. Methods: A prospective review of all patients with arterial and venous injuries being transferred to the Trauma Center at out Tertiary Care Center between June 2015 and May 2018 was done. Demographics, admission data, treatment, and complications were reviewed. Results: There were a total of 46 patients with 65 vascular injuries, 39 arterial injuries and 26 venous injuries. The age range was 21 to 47 years. Nineteen patients had both arterial and venous injuries. A total of 42 cases presented within 12 hours of injury and complete arterial transections were found in 33 cases (80.49%). There were three mortalities (6.52%) and three amputations (8.33%). The overall limb salvage rate was 91.67% with popliteal artery being the commonest injured artery. Poor prognosticators for limb salvage were increasing time to present to the trauma centre, hypovolemic shock, multi-organ trauma and associated venous injuries. Conclusions: Penetrating missile trauma leading to vascular injuries has not been widely reported. Attempting limb salvage even in cases with delayed presentation should be weighed with the threat to life before revascularisation and should preferably be done at a centre with vascular expertise. A team approach with vascular, orthopaedic, general surgeons, and critical care anaesthesiologists all aboard improve the outcomes manifold. Use of tourniquets and early fasciotomies have been emphasized as is the use of native veins as the bypass conduit. This is probably the largest study on penetrating Vascular trauma in anti-terrorism ops from the Indian subcontinent. It highlights the significance of prompt recognition and availability of vascular expertise in optimally managing cases of vascular trauma.

Parkinson's disease diagnosis using speech signal and deep residual gated recurrent neural network (음성 신호와 심층 잔류 순환 신경망을 이용한 파킨슨병 진단)

  • Shin, Seung-Su;Kim, Gee Yeun;Koo, Bon Mi;Kim, Hyoung-Gook
    • The Journal of the Acoustical Society of Korea
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    • v.38 no.3
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    • pp.308-313
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    • 2019
  • Parkinson's disease, one of the three major diseases in old age, has more than 70 % of patients with speech disorders, and recently, diagnostic methods of Parkinson's disease through speech signals have been devised. In this paper, we propose a method of diagnosis of Parkinson's disease based on deep residual gated recurrent neural network using speech features. In the proposed method, the speech features for diagnosing Parkinson's disease are selected and applied to the deep residual gated recurrent neural network to classify Parkinson's disease patients. The proposed deep residual gated recurrent neural network, an algorithm combining residual learning with deep gated recurrent neural network, has a higher recognition rate than the traditional method in Parkinson's disease diagnosis.

The process of estimating user response to training stimuli of joint attention using a robot (로봇활용 공동 주의 훈련자극에 대한 사용자 반응상태를 추정하는 프로세스)

  • Kim, Da-Young;Yun, Sang-Seok
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.10
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    • pp.1427-1434
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    • 2021
  • In this paper, we propose a psychological state estimation process that computes children's attention and tension in response to training stimuli. Joint attention was adopted as the training stimulus required for behavioral intervention, and the Discrete trial training (DTT) technique was applied as the training protocol. Three types of training stimulation contents are composed to check the user's attention and tension level and provided mounted on a character-shaped tabletop robot. Then, the gaze response to the user's training stimulus is estimated with the vision-based head pose recognition and geometrical calculation model, and the nervous system response is analyzed using the PPG and GSR bio-signals using heart rate variability(HRV) and histogram techniques. Through experiments using robots, it was confirmed that the psychological response of users to training contents on joint attention could be quantified.