• Imaging Science in Dentistry
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• 제51권2호
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• pp.187-193
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• 2021

Purpose: This study aimed to assess the usefulness of machine learning and automation techniques to match pairs of panoramic radiographs for personal identification. Materials and Methods: Two hundred panoramic radiographs from 100 patients (50 males and 50 females) were randomly selected from a private radiological service database. Initially, 14 linear and angular measurements of the radiographs were made by an expert. Eight ratio indices derived from the original measurements were applied to a statistical algorithm to match radiographs from the same patients, simulating a semi-automated personal identification process. Subsequently, measurements were automatically generated using a deep neural network for image recognition, simulating a fully automated personal identification process. Results: Approximately 85% of the radiographs were correctly matched by the automated personal identification process. In a limited number of cases, the image recognition algorithm identified 2 potential matches for the same individual. No statistically significant differences were found between measurements performed by the expert on panoramic radiographs from the same patients. Conclusion: Personal identification might be performed with the aid of image recognition algorithms and machine learning techniques. This approach will likely facilitate the complex task of personal identification by performing an initial screening of radiographs and matching ante-mortem and post-mortem images from the same individuals.

• 스마트미디어저널
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• 제8권2호
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• pp.66-73
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• 2019

최근 컴퓨터 비전을 활용한 사물인식 기술이 센서 기반 사물인식 기술을 대체할 기술로 주목을 받고 있다. 센서 기반 사물인식 기술은 일반적으로 고가의 센서를 필요로 하기 때문에 기술이 상용화되기 어렵다는 문제가 있었다. 반면 컴퓨터 비전을 활용한 사물인식 기술은 고가의 센서 대신 비교적 저렴한 카메라를 사용할 수 있다. 동시에 CNN이 발전하면서 실시간 사물인식이 가능해진 이후 IoT, 자율주행자동차 등 타 분야에 활발하게 도입되고 있다. 그러나 사물 인식 모델을 상황에 알맞게 선택하고 학습시키기 위해서는 딥러닝에 대한 전문적인 지식을 요구하기 때문에 비전문가가 사물 인식 모델을 사용하기에는 어려움이 따른다. 따라서 본 논문에서는 딥러닝 기반 사물인식 모델들의 구조와 성능을 분석하고, 사용자가 원하는 조건의 최적의 딥러닝 기반 사물 인식 모델을 스스로 선정할 수 있는 플랫폼을 제안한다. 또한 통계에 기반한 사물 인식 모델 선정이 필요한 이유를 실험을 통해 증명한다.

• Korean Chemical Engineering Research
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• 제55권4호
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• pp.497-502
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• 2017

Estimation of accident cost is a sound and great safety indicator on determining accurate occupational safety and health prevention. Just like in Korea, Heinrich ratio analysis of (1:4) between direct and indirect costs has been become widely used in safety management because of its simplicity. In this study four major categories of uninsured (indirect) cost items and 18 sub-categories of uninsured (indirect) cost items were identified. To determine and validate the importance and necessity of the results of a literature review an expert or professional surveyed had been analyses using the SPSS 18.0, where in the participants whose expertize is in the field of compensation and safety. Based on the results of survey all participants all uninsured (indirect) cost items classified was important and necessary when accidents occurred. Despite recognition of expert on the classification of uninsured (indirect) cost items, it is quite difficult to make generalization for all kind of costs in occupational accident case due to different nature of business for each industry.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 1996년도 International Conference on Agricultural Machinery Engineering Proceedings
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• pp.773-779
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• 1996

Dried oak mushroom have complex and various visual features. Grading and sorting of dried oak mushrooms has been done by the human expert. Though actions involved in human grading looked simple, a decision making underneath the simple action comes from the result of the complex neural processing of the visual image. Through processing details involved in human visual recognition has not been fully investigated yet, it might say human can recognize objects via one of three ways such as extracting specific features or just image itself without extracting those features or in a combined manner. In most cases, extracting some special quantitative features from the camera image requires complex algorithms and processing of the gray level image requires the heavy computing load. This fact can be worse especially in dealing with nonuniform, irregular and fuzzy shaped agricultural products, resulting in poor performance because of the sensitiveness to the crisp criteria or specific ules set up by algorithms. Also restriction of the real time processing often forces to use binary segmentation but in that case some important information of the object can be lost. In this paper, the neuro net based real time recognition algorithm was proposed without extracting any visual feature but using only the directly captured raw gray images. Specially formated adaptable size of grids was proposed for the network input. The compensation of illumination was also done to accomodate the variable lighting environment. The proposed grading scheme showed very successful results.

• 한국산림과학회지
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• 제99권4호
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• pp.645-653
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• 2010

본 연구는 국립공원에서의 산림에 대하여 적절한 관리에 관한 인식과 그 방향에 대하여 분석하기 위해 생태 및 산림전문가를 대상으로 국립공원 내 산림시업에 관한 인식에 대하여 설문조사를 실시하였다. 그런 다음, 통계 분석을 이용하여 분석한 결과, 응답자들은 국립공원 내 산림 관리에 대해 응답자 유형간의 차이가 있었다. 그러나 그 유형과는 무관하게 국립공원의 산림관리에 대해 모두 필요하다고 인식하고 있는 것으로 나타나 산림과 관련된 전문기관 및 전문가에 의한 관리가 필요한 것으로 분석되었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권11호
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• pp.2016-2034
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• 2011

Ubiquitous Healthcare (u-Healthcare) is the intelligent delivery of healthcare services to users anytime and anywhere. To provide robust healthcare services, recognition of patient daily life activities is required. Context information in combination with user real-time daily life activities can help in the provision of more personalized services, service suggestions, and changes in system behavior based on user profile for better healthcare services. In this paper, we focus on the intelligent manipulation of activities using the Context-aware Activity Manipulation Engine (CAME) core of the Human Activity Recognition Engine (HARE). The activities are recognized using video-based, wearable sensor-based, and location-based activity recognition engines. An ontology-based activity fusion with subject profile information for personalized system response is achieved. CAME receives real-time low level activities and infers higher level activities, situation analysis, personalized service suggestions, and makes appropriate decisions. A two-phase filtering technique is applied for intelligent processing of information (represented in ontology) and making appropriate decisions based on rules (incorporating expert knowledge). The experimental results for intelligent processing of activity information showed relatively better accuracy. Moreover, CAME is extended with activity filters and T-Box inference that resulted in better accuracy and response time in comparison to initial results of CAME.

• 한국정보통신학회논문지
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• 제24권2호
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• pp.297-303
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• 2020

이 연구에서는 2015 개정교육과정의 소프트웨어교육에 대한 초보 교사와 전문가 교사 대상 인식을 비교하였다. 인식 비교는 현장 지원을 위한 우선 순위, 전문성 신장을 위한 활동 내용, 편제 시수, 성취 기준 진술 내용, 6학년에만 도입된 교과서에 대한 적절성을 설문을 통해 알아보았다. 모든 문항에서 두 그룹의 인식 차이가 있음을 확인하였다. 특히 편제 시수, 성취 기준 진술 내용, 6학년에만 도입된 교과서에 대한 의견에서 초보 교사는 '적절하다'라는 의견이 많았다. 반면, 전문가 교사는 '부적절하다'가 많았다. 아울러 실과 교육과정과 교과서에 교육용 로봇이 도입된 것에 대한 자유 응답식 의견의 주요 키워드를 분석할 결과 두 그룹 모두 긍정적인 키워드가 도출되었다. 그러나 초보 교사들은 '지원', '어려움', '문제'와 같은 수동적이고 소극적인 키워드, 전문가 교사들은 '활용', '교육' 등 도입 후 교육적인 활용 부분에 대해 키워드가 도출되어 차이점을 보였다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2000년도 추계학술대회 논문집
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• pp.303-306
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• 2000

This paper describes a research on the development of the 3D design automation system for progressive die. Based on knowledge base of expert, this system can carry out design tasks, such as feature recognition of product data, layout design, dre set component design. Easy system user mterface and 3-dlmensional solid modeling could result in time and cost saving.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1989년도 한국자동제어학술회의논문집; Seoul, Korea; 27-28 Oct. 1989
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• pp.290-295
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• 1989

This paper proposes a Expert CAPP System for integrating CAD/CAM of rotational work-part by rule based approach. The CAD/CAPP integration is performed by the recognition of machined features from the 2-D CAD data (IGES) file. Selecting functions of the process planning are performed in modularized rule base by forward chaining inference, and operation sequences are determined by means of heuristic search algorithm. For CAPP/CAM integration, post-processor generates NC code from route sheet file. This system coded in OPS5 and C language on PC/AT, and EMCO CNC lathe interfaced with PC through DNC and RS-232C.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 하계학술대회 논문집 B
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• pp.787-790
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• 1995

This paper proposes a method to recognize object with 2-dimension image. In most cases, it takes too many processes, complicate algorithm and time to recognize object with expert system because of inherent comfiguration of the object. This paper includes some processing steps such as pre-processing method, recognition method with neural network and learing algorithm of multi-layer perceptron using error backpropagation.