• 제목/요약/키워드: Experimental Category

검색결과 241건 처리시간 0.029초

의복범주가 젊은이의 대인지각에 미치는 영향 -유행성 및 착용자의 체형과 관련지어- (The Effect of Garment Category, Fashionability and Wears' Body type on Impression Formation)

  • 김재숙;김희숙
    • 한국의류학회지
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    • 제16권4호
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    • pp.371-377
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    • 1992
  • The purposes of the study were 1) to extend the cognitive categorization theory in an attempt to explain the of garment category, fashionability, and wearer's body types on impression formation, and 2) to find out structures of wearer's impressional dimension and wearer's professional image. The research included a quasi-experiment and survey. The experimental design was a $2^{3}$full factorial design of 3 independent variables. The experimental materials developed for the study were a set of stimuli and a response scale. The stimuli consisted of 8 drawings made by 3 independent variables (garment category, fashion level, wearer's body type). Result were as follows: 1) Garment category, fashionability and wearer's body type had significant effects on impression of the 5 factors-evaluation, potency, appearance, sociability and good-bad, with exception of wearer's body type which was nonsignificant to the potency factor. 2) Garment category was most effective on the evaluation and the potency. However wearer's body type was most effect on the appearance factor and fashionability variable was most effective on the good-bad factor. It was conclued that the results supported the cognitive categorization theory on impression formation and a cognitive categorization hypothesis of clothes.

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Affine Category Shape Model을 이용한 형태 기반 범주 물체 인식 기법 (A New Shape-Based Object Category Recognition Technique using Affine Category Shape Model)

  • 김동환;최유경;박성기
    • 로봇학회논문지
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    • 제4권3호
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    • pp.185-191
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    • 2009
  • This paper presents a new shape-based algorithm using affine category shape model for object category recognition and model learning. Affine category shape model is a graph of interconnected nodes whose geometric interactions are modeled using pairwise potentials. In its learning phase, it can efficiently handle large pose variations of objects in training images by estimating 2-D homography transformation between the model and the training images. Since the pairwise potentials are defined on only relative geometric relationship betweenfeatures, the proposed matching algorithm is translation and in-plane rotation invariant and robust to affine transformation. We apply spectral matching algorithm to find feature correspondences, which are then used as initial correspondences for RANSAC algorithm. The 2-D homography transformation and the inlier correspondences which are consistent with this estimate can be efficiently estimated through RANSAC, and new correspondences also can be detected by using the estimated 2-D homography transformation. Experimental results on object category database show that the proposed algorithm is robust to pose variation of objects and provides good recognition performance.

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Document Classification Model Using Web Documents for Balancing Training Corpus Size per Category

  • Park, So-Young;Chang, Juno;Kihl, Taesuk
    • Journal of information and communication convergence engineering
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    • 제11권4호
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    • pp.268-273
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    • 2013
  • In this paper, we propose a document classification model using Web documents as a part of the training corpus in order to resolve the imbalance of the training corpus size per category. For the purpose of retrieving the Web documents closely related to each category, the proposed document classification model calculates the matching score between word features and each category, and generates a Web search query by combining the higher-ranked word features and the category title. Then, the proposed document classification model sends each combined query to the open application programming interface of the Web search engine, and receives the snippet results retrieved from the Web search engine. Finally, the proposed document classification model adds these snippet results as Web documents to the training corpus. Experimental results show that the method that considers the balance of the training corpus size per category exhibits better performance in some categories with small training sets.

그래프 구조를 이용한 카테고리 구조로부터 상하위 관계 추출 (Graph-based ISA/instanceOf Relation Extraction from Category Structure)

  • 최동현;최기선
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제37권6호
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    • pp.464-469
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    • 2010
  • 상하위 관계 자동 추출은 분류체계를 자동 구축하는 데 있어서 핵심적인 내용이며, 이렇게 자동으로 구축된 분류 체계는 정보 추출과 같은 여러 가지 분야에 있어서 중요하게 사용된다. 본 논문에서는 카테고리 구조로부터 상하위 관계를 추출하는 방식에 대하여 제안한다. 본 논문에서는 판별하고자 하는 카테고리 구조뿐만이 아닌, 그와 관련된 다른 카테고리 구조까지 고려하여 카테고리 이름에 나타난 토큰들간의 수식 그래프를 구축한 후, 그래프 분석 알고리즘을 통하여 각 카테고리 구조가 상하위 관계일 가능성에 대한 점수를 매긴다. 실험 결과, 본 알고리즘은 기존의 연구로 상하위 관계임을 판별할 수 없었던 일부 카테고리 구조에 대하여 성공적으로 상하위 관계인지를 판별하였다.

Decomposition of category mixture in a pixel and its application for supervised image classification

  • Matsumoto, Masao;Arai, Kohei;Ishimatsu, Takakazu
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 19-21 Oct. 1992
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    • pp.514-519
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    • 1992
  • To make an accurate retrieval of the proportion of each category among mixed pixels (Mixel's) of a remotely sensed imagery, a maximum likelihood estimation method of category proportion is proposed. In this method, the observed multispectral vector is considered as probability variables along with the approximation that the supervised data of each category can be characterized by normal distribution. The results show that this method can retrieve accurate proportion of each category among Mixel's. And a index that can estimate the degree of error in each category is proposed. AS one of the application of the proportion estimation, a method for image classification based on category proportion estimation is proposed. In this method all pixel in a remotely sensed imagery are assumed to be Mixel's, and are classified to most dominant category. Among the Mixel's, there exists unconfidential pixels which should be categorized as unclassified pixels. In order to discriminate them, two types of criteria, Chi square and AIC, are proposed for fitness test on pure pixel hypothesis. Experimental result with a simulated dataset show an usefulness of proposed classification criterion compared to the conventional maximum likelihood criterion and applicability of the fitness tests based on Chi square and AIC,

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Personalized Anti-spam Filter Considering Users' Different Preferences

  • Kim, Jong-Wan
    • 한국멀티미디어학회논문지
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    • 제13권6호
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    • pp.841-848
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    • 2010
  • Conventional filters using email header and body information equally judge whether an incoming email is spam or not. However this is unrealistic in everyday life because each person has different criteria to judge what is spam or not. To resolve this problem, we consider user preference information as well as email category information derived from the email content. In this paper, we have developed a personalized anti-spam system using ontologies constructed from rules derived in a data mining process. The reason why traditional content-based filters are not applicable to the proposed experimental situation is described. In also, several experiments constructing classifiers to decide email category and comparing classification rule learners are performed. Especially, an ID3 decision tree algorithm improved the overall accuracy around 17% compared to a conventional SVM text miner on the decision of email category. Some discussions about the axioms generated from the experimental dataset are given too.

Application of a Deep Learning Method on Aerial Orthophotos to Extract Land Categories

  • Won, Taeyeon;Song, Junyoung;Lee, Byoungkil;Pyeon, Mu Wook;Sa, Jiwon
    • 한국측량학회지
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    • 제38권5호
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    • pp.443-453
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    • 2020
  • The automatic land category extraction method was proposed, and the accuracy was evaluated by learning the aerial photo characteristics by land category in the border area with various restrictions on the acquisition of geospatial data. As experimental data, this study used four years' worth of published aerial photos as well as serial cadastral maps from the same time period. In evaluating the results of land category extraction by learning features from different temporal and spatial ranges of aerial photos, it was found that land category extraction accuracy improved as the temporal and spatial ranges increased. Moreover, the greater the diversity and quantity of provided learning images, the less the results were affected by the quality of images at a specific time to be extracted, thus generally demonstrating accurate and practical land category feature extraction.

패션브랜드 확장 시 확장제품군 내 지배적 브랜드가 확장제품의 호의도에 미치는 영향 - 경쟁 브랜드 간 품질차이와 소비자 자기관을 중심으로 - (The Influences of Dominant Brand in the Extension Product Category on Consumer Attitude About Fashion Brand Extension)

  • 곽지혜;황선진
    • 복식
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    • 제61권10호
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    • pp.89-103
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    • 2011
  • The purpose of this study is to analyze the effects of dominant brand, the quality variation among brands in the extension product category and the self-construals on consumer's attitude about extension products. The experimental design consist of three-way complex factors and 226 subjects participated for the study. The results showed that when there was fashion brand extension, whether or not there was an existing dominant brand in the extension product category, the quality variation among brands in the extension product category and the types of self-construals had a significant interaction effect on their favorableness and intention to purchase the extension products. Regardless of an existing dominant brand however, the group who had an interdependent self-construal showed higher favorableness and intention to purchase the extension products when the quality variation among brands in the extension product category was lower than when it was high, whereas the group who had an independent self-construal showed no significant difference of the favorableness and intention to purchase the extension products.

Thinking Science 프로그램 중 분류활동이 초등학교 5학년 학생의 분류문제해결능력에 미치는 영향 (The Effect of the classification problem solving of Thinking Science Program on the Classified Activities on Elementary School 5th grade category)

  • 이성현;한신
    • 대한지구과학교육학회지
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    • 제4권2호
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    • pp.102-107
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    • 2011
  • In this study, elementary school science program, this category did not affect any troubleshooting analyzed. Thinking Science Program to buy for them in group activities by using one of the elements of a program of treatment and cognitive level effects were two kinds of research questions. 102, 5th grade four classes were involved, these two classes of the experimental group and the remaining two classes were divided into a control group. Pre-test between the two groups is compared to the level and classification problem-solving skills but the skills did not show a statistically significant difference. Thinking Science activity after application of classification and posttest the experimental group than in the control group problem solving abilities of students classified at the level of statistical significance was higher. Thinking Science program is a treatment effect for each level of analysis, tests, regardless of cognitive level was more effective. Through theses findings, Thinking Science activities 5th grade category classification problem-solving skills of students found to be effective in improving and these types of programs actively introduced in the field suggests that we need to see.

용액 개념의 순환학습이 초등학생의 인지수준발달에 미치는 영향 (The Effect of Learning Cycle Model in Solution Concept on the Cognitive Development for Primary Student)

  • 최영주;김세경;고영신
    • 한국초등과학교육학회지:초등과학교육
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    • 제23권4호
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    • pp.273-278
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    • 2004
  • According to Piaget, children aged 11 are in the middle of concrete operation period and formal operation period. So, it is necessary to adopt the Learning Cycle Model (LCM) which helps students improve their cognitive development. After determining the test for the Science Concept of Matter (SCOM), the experimental group showed higher average than the comparative group in the post-test. In the sound understanding, the experimental group showed higher ratio than the comparative group. And in the ratio of imperfect, wrong understanding and no response, the experimental group was lower than the comparative group. On the questions that were needed the complicated inquiry, many students of both groups still couldn't find the fundamental cause. In forming the scientific conceptualization, there was a meaningful difference (p < .001) after post-test Analysis of Covariance (ANCOVA) with pre-test result. After determining the test for the Test Inquiry Science Process (TISP), the experimental group showed higher average than the comparative group in the post-test. In the category of basic inquiry process which is needed in concrete operation, there was a meaningful difference (p < .05). In the category of unified inquiry process which is needed in formal operation, they showed no meaningful difference (p > .05). Therefore, applying the LCM to the chapter of 'Solution and Dissolving' is more effective on improving the scientific conceptualization and on helping the concrete operation abilities than the teacher centered learning.

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