• 제목/요약/키워드: a priori knowledge

검색결과 168건 처리시간 0.032초

Tracking Object of Snake based on the Refinement using 5 Point Invariant

  • Kim, Won;Lee, Ju-Jang
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2001년도 ICCAS
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    • pp.24.3-24
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    • 2001
  • In cases where strong a priori knowledge about the object being analyzed is available, it can be embedded into the formulation of the snake model. When prior knowledge of shape is available for a specific application, information concerning the shape of the desired objects can be incorporated into the formulation of the snake model as an active contour model. In this paper we show Five points algorithm can be applied to design invariant energy.

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내장 문자와 사전 구조 지식을 이용한 HTMLtoVXML 변환 에이전트 개발 (Development of HTMLtoVTML Conversion Agent using Embedded Text and Priori Structural Knowledge)

  • 장영건
    • 정보처리학회논문지D
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    • 제10D권2호
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    • pp.343-350
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    • 2003
  • 본 연구는 음성 인터넷 서비스를 위하여 기존의 HTML 컨텐츠를 자동으로 VXML 컨텐츠로 변환하여 사용하는 방법에 관한 것이다. 문서 변환은 HTML 문서의 해석과 내용 분리에 앞서 컨텐츠의 선택이 필수적으로 요구되지만, 이미 알고 있고, 관심이 있는 내용의 집단적 선택에 대하여는 아직까지 좋은 해법이 없어 보인다. 본 논문에서는 비구조적 데이터로 구성된 웹 문서로부터 필요한 정보 묶음을 선택하기 위하여 웹 문서에 포함된 문자열, 구조에 대한 사용자의 사전 지식을 상호 반응적으로 사용하는 방법을 제안하며, 이를 구현하여 그 타당성을 입증하였다. 제안하는 방식은 기존의 구조적 방식에 의한 선택보다 사용자의 의도를 정확히 반영하며, 문서 표현의 구현 기법의 변화에 강건한 장점이 있다. 또한 컨텐츠 분리 측면에서는 XML또는 XHTML 문서변환을 중간 과정으로 사용하는 방식에 비하여 시간적으로 빠르며, 변환 과정의 부담이 작다.

선험적 지식으로서 곱셈의 교환법칙 교육의 문제 (Commutative Property of Multiplication as a priori Knowledge)

  • 임재훈
    • 한국초등수학교육학회지
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    • 제18권1호
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    • pp.1-17
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    • 2014
  • 초등학교에서 곱셈의 교환법칙의 지도는 $3{\times}4=12$, $4{\times}3=12$와 같이 $a{\times}b$$b{\times}a$ 의 값을 계산하고 실제로 그 값이 같은지를 확인하는 활동을 바탕으로 하는 것이 보통이다. 이 논문에서는 첫째로, 순수이성비판에 나타난 수학적 지식에 관한 칸트의 견해를 바탕으로, 곱셈의 교환법칙의 취급 방법을 비판적으로 고찰한다. 칸트에 의하면, 수학적 지식은 선험성과 도식성이라는 특징을 지니고 있다. 두 곱셈의 계산 결과를 비교하는 방법은 선험성과 도식성이라는 수학적 지식의 특성을 충족하지 못한다. 칸트의 관점에서 볼 때, $a{\times}b$$b{\times}a$ 로 변환하는 필연적이고 일반적인 도식이 드러나게 교환법칙을 취급하는 것이 적절하다. 둘째로, 곱셈의 교환법칙의 도식과 관련된 기본구성단위로의 분배 전략은 (자연수)${\times}$(10의 거듭제곱), 몫 분수 맥락에서 분수의 복합적 의미, 분수의 곱셈과 같은 학습 내용을 관통하는 일반적인 성격의 것임을 논한다. 끝으로, 이상의 두 논의를 바탕으로 초등 수학교과서에서 곱셈의 교환법칙이 다루어지는 방식을 비판적으로 고찰한다.

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Managing Complexity in Object-Oriented Analysis

  • Ine, So-Ran;Youn, Cheong;Misbah, Uddin Mirza;Lee, Kwon-Il;Cha, Seung-Hoon;Byoun, Bo-Gyun;Bae, Doo-Hwan
    • ETRI Journal
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    • 제20권2호
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    • pp.192-213
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    • 1998
  • The current approaches in Object-Oriented Analysis have limitations on modeling complex real world systems because they require priori knowledge about objects and their interactions before applying them. This may be practical in small systems and systems with clear domain knowledge, but not in large real world systems with unclear domain knowledge. Our approach uses a stepwise refinement technique in a top-down manner to the Object-Oriented Analysis stage with the application of use cases. This approach is especially good for new areas where we do not know all the information in advance. We present the approach with an example of its application to the B-ISDN service modeling and distributed systems.

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FUZZY HYPERCUBES: A New Inference Machines

  • Kang, Hoon
    • 한국지능시스템학회논문지
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    • 제2권2호
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    • pp.34-41
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    • 1992
  • A robust and reliable learning and reasoning mechanism is addressed based upon fuzzy set theory and fuzzy associative memories. The mechanism stores a priori an initial knowledge base via approximate learning and utilizes this information for decision-making systems via fuzzy inferencing. We called this fuzzy computer architecture a 'fuzzy hypercube' processing all the rules in one clock period in parallel. Fuzzy hypercubes can be applied to control of a class of complex and highly nonlinear systems which suffer from vagueness uncertainty. Moreover, evidential aspects of a fuzzy hypercube are treated to assess the degree of certainty or reliability together with parameter sensitivity.

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Detecting Object of Interest from a Noisy Image Using Human Visual Attention

  • Cheoi Kyung-Joo
    • International Journal of Contents
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    • 제2권1호
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    • pp.5-8
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    • 2006
  • This paper describes a new mechanism of detecting object of interest from a noisy image, without using any a-priori knowledge about the target. It employs a parallel set of filters inspired upon biological findings of mammalian vision. In our proposed system, several basic features are extracted directly from original input visual stimuli, and these features are integrated based on their local competitive relations and statistical information. Through integration process, unnecessary features for detecting the target are spontaneously decreased, while useful features are enhanced. Experiments have been performed on a set of computer generated and real images corrupted with noise.

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Rank Reduction for Wideband Signals incident on a Uniform Linear Array

  • Hong, Wooyoung
    • 한국음향학회:학술대회논문집
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    • 한국음향학회 1992년도 학술논문발표회 논문집 제11권 1호
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    • pp.123-126
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    • 1992
  • A new class of data transformation matri is introduced for estimation of angles of arrivals by the rank reduction of multiple wideband sources. The proposed unitary focusing matri minimizes the average of the squared norm of focusing error over the angles of interest without a priori knowledge of source locations. The merit that result as a consequence is a lower resolution threshold. These matrices can be applied to the case of the multigroup sources. Simulations and the comparison of statistical performance are compared with the algorithms (especially, spatial resampling method) which does not require the pre-estimation.

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영상처리 시스템을 이용한 그림조각 맞추기에 관한 연구 (A Vision-Based Jig-Saw Puzzle Matching Method)

  • 이동주;서일홍;오상록
    • 대한전자공학회논문지
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    • 제27권1호
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    • pp.96-104
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    • 1990
  • In this paper, a novel method of jig-saw puzzle matching is proposed using a modifided boundary matching algorithm without a priori knowledge for the matched puzzle. Specifically, a boundary tracking algorithm is utilised to segment each puzzle from low-resolution image data. Segmented puzzle is described via corner point, angle and distance between two adjacent coner point, and convexity and/or concavity of corner point. Proposed algorithm is implemented and tested in IBM PC and PC version vision system, and applied successfully to real jig-saw puzzles.

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동적 환경에서 강화학습을 이용한 다중이동로봇의 제어 (Reinforcement learning for multi mobile robot control in the dynamic environments)

  • 김도윤;정명진
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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    • pp.944-947
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    • 1996
  • Realization of autonomous agents that organize their own internal structure in order to behave adequately with respect to their goals and the world is the ultimate goal of AI and Robotics. Reinforcement learning gas recently been receiving increased attention as a method for robot learning with little or no a priori knowledge and higher capability of reactive and adaptive behaviors. In this paper, we present a method of reinforcement learning by which a multi robots learn to move to goal. The results of computer simulations are given.

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Opportunistic Spectrum Access Based on a Constrained Multi-Armed Bandit Formulation

  • Ai, Jing;Abouzeid, Alhussein A.
    • Journal of Communications and Networks
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    • 제11권2호
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    • pp.134-147
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    • 2009
  • Tracking and exploiting instantaneous spectrum opportunities are fundamental challenges in opportunistic spectrum access (OSA) in presence of the bursty traffic of primary users and the limited spectrum sensing capability of secondary users. In order to take advantage of the history of spectrum sensing and access decisions, a sequential decision framework is widely used to design optimal policies. However, many existing schemes, based on a partially observed Markov decision process (POMDP) framework, reveal that optimal policies are non-stationary in nature which renders them difficult to calculate and implement. Therefore, this work pursues stationary OSA policies, which are thereby efficient yet low-complexity, while still incorporating many practical factors, such as spectrum sensing errors and a priori unknown statistical spectrum knowledge. First, with an approximation on channel evolution, OSA is formulated in a multi-armed bandit (MAB) framework. As a result, the optimal policy is specified by the wellknown Gittins index rule, where the channel with the largest Gittins index is always selected. Then, closed-form formulas are derived for the Gittins indices with tunable approximation, and the design of a reinforcement learning algorithm is presented for calculating the Gittins indices, depending on whether the Markovian channel parameters are available a priori or not. Finally, the superiority of the scheme is presented via extensive experiments compared to other existing schemes in terms of the quality of policies and optimality.