• 충청수학회지
• /
• 제20권3호
• /
• pp.327-332
• /
• 2007

A variational inequality defined by the second-order cone is considered, and it is shown that a necessary and sufficient condition for a solution of the variational inequality holds under some regularity condition.

• 대한수학회지
• /
• 제35권1호
• /
• pp.237-257
• /
• 1998

By introducing the notion of a generalized normal state space, we give a necessary and sufficient condition for that there exists a unital normal completely map from a von Neumann algebra into another, in terms of their generalized normal state spaces.

• 한국측량학회지
• /
• 제40권4호
• /
• pp.293-304
• /
• 2022

본 연구에서는 고해상도 위성영상의 상대기하보정 결과에 건물이 미치는 영향을 분석하기 위해 건물에서 추출된 정합쌍의 유무에 따른 상대기하보정 결과를 비교한다. 건물 정합쌍의 제거를 위해 수치지형도에서 건물 객체를 추출하여 생성한 건물마스크 영상을 이용하였으며, 추가적으로 수렴각의 크기에 따른 정합쌍 추출 성능 및 상대기하보정 결과를 분석하였다. Affine 및 Piecewise linear 변환모델을 각각 적용하여 건물밀집지역에 대한 상대기하보정 결과를 비교하였다. 실험 결과, Affine 변환모델은 건물 정합쌍 제거 후 전반적인 정확도 향상을 나타내었다. 반면에, Piecewise linear 변환모델은 주변에 건물을 포함하고 있는 검사점에서 정확도가 향상되었으나, 건물이 없는 평탄한 지역의 검사점에서는 정확도 향상이 크지 않았다. 또한, Piecewise linear 변환모델을 적용할 경우 20° 이하의 수렴각을 갖는 영상에서 2 pixels 이하의 안정적인 정확도를 도출하였다.

• 대한기계학회:학술대회논문집
• /
• 대한기계학회 2005년도 창립60주년 기념 추계 학술대회
• /
• pp.201.2-201.2
• /
• 2005

• East Asian mathematical journal
• /
• 제15권2호
• /
• pp.277-290
• /
• 1999

In this paper, we investigate the existence of a two dimensional surface in a four dimensional equiaffine space and characterize that surface.

• 한국정보과학회논문지:데이타베이스
• /
• 제36권6호
• /
• pp.446-454
• /
• 2009

다양한 영역 검출 및 형태 특징 추출 방법 중에서 MSER과 SIFT를 응용한 방법들이 컴퓨터비전 분야에 많이 사용된다. 하지만 기존의 SIFT를 이용한 특징 추출 방법은 자기 변화에 민감한 특성을 지니며, MSER 방법은 이미지의 크기 변화에 민감하고, 이미지 유사성 검색에 그대로 적용하기에는 어려움이 많다. 본 논문에서는 스케일 피라미드, MSER 그리고 어파인(affine) 정규화 과정 등을 이용한 영역 특징 서술자를 제안한다. 제안한 방법은 어파인 정규화 방법과 스케일 피라미드를 사용하기 때문에 이미지의 크기, 회전 및 자기 변화에 불변하다. 다양한 이미지들을 이용하여 실험하고, 실험 결과에서 제안한 방법이 SIFT, PCA-SIFT, CE-SIFT 그리고 SURF 방법에 비해서 각각 20%, 38%, 11%, 24% 이상 좋은 이미지 검색 성능을 보이고 있다.

• 전자공학회논문지C
• /
• 제35C권2호
• /
• pp.56-64
• /
• 1998

Multi-layered perceptrons that are a nonlinear neural network model, have been widely used for various applications mainly thanks to good function approximation capability for nonlinear fuctions. However, for digital hardware implementation of the multi-layere perceptrons, the quantization scheme using "look-up tables (LUTs)" is commonly employed to handle nonlinear signmoid activation functions in the neworks, and thus requires large amount of storage to prevent unacceptable quantization errors. This paper is concerned with a new effective methodology for digital hardware implementation of multi-layered perceptrons, and proposes a "piecewise affine approximation" method in which input domain is divided into (small number of) sub-intervals and nonlinear sigmoid function is linearly approximated within each sub-interval. Using the proposed method, we develop an expression and an error backpropagation type learning algorithm for a multi-layered perceptron, and compare the performance with the quantization method through Monte Carlo simulations on XOR problems. Simulation results show that, in terms of learning convergece, the proposed method with a small number of sub-intervals significantly outperforms the quantization method with a very large storage requirement. We expect from these results that the proposed method can be utilized in digital system implementation to significantly reduce the storage requirement, quantization error, and learning time of the quantization method.quantization method.

• 한국측량학회지
• /
• 제34권2호
• /
• pp.133-142
• /
• 2016

KOMPSAT-3A (KOrea Multi-Purpose SATellite-3A) was launched in March 25 2015 with specification of 0.5 meters resolution panchromatic and four 2.2 meters resolution multi spectral sensors in 12km swath width at nadir. To better understand KOMPSAT-3A positional accuracy, this paper reports a test result on the accuracy of recently released KOMPSAT-3A beta test images. A number of ground points were acquired from 1:1,000 digital topographic maps over the target area for the accuracy validation. First, the original RPCs (Rational Polynomial Coefficients) were validated without any GCPs (Ground Control Points). Then we continued the test by modeling the errors in the image space using shift-only, shift and drift, and the affine model. Ground restitution accuracy was also analyzed even though the across track image pairs do not have optimal convergence angle. The experimental results showed that the shift and drift-based RPCs correction was optimal showing comparable accuracy of less than 1.5 pixels with less GCPs compared to the affine model.

• Journal of Electrical Engineering and Technology
• /
• 제13권2호
• /
• pp.943-952
• /
• 2018

This paper presents a new type of absolute rotary encoder system based on the affine n-digit N-ary gray code. A brief comparison of the existing encoder systems is carried out in terms of resolution, encoding and decoding principles and number of sensor heads needed. Using the proposed method, two different types of encoder disks are designed, namely, color-coded disk and grayscale coded disk. The designed coded disk pattern is used to manufacture 3 digit 3 ary and 2 digit 5 ary grayscale coded disks respectively. The manufactured disk is used with the light emitter and photodetector assembly to design the entire encode system. Experimental analysis is done on the designed prototype with LabVIEW platform for data acquisition. A comparison of the designed system is done with the traditional binary gray code encoder system in terms of resolution, disk diameter, number of tracks and data acquisition system. The resolution of the manufactured system is 3 times higher than the conventional system. Also, for a 5 digit 5 ary coded encoder system, a resolution approximately 100 times better than the conventional binary system can be achieved. In general, the proposed encoder system gives $(N/2)^n$ times better resolution compared with the traditional gray coded disk. The miniaturization in diameter of the coded disk can be achieved compared to the conventional binary systems.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제18권8호
• /
• pp.2298-2315
• /
• 2024

This paper introduces a method aimed at diagnosing the presence or absence of lesions by detecting anomalies in Chest X-ray images. The proposed approach is based on the PatchCore anomaly detection method, which extracts a feature vector containing location information of an image patch from normal image data and calculates the anomaly distance from the normal vector. However, applying PatchCore directly to medical image processing presents challenges due to the possibility of diseases occurring only in specific organs and the presence of image noise unrelated to lesions. In this study, we present an image alignment method that utilizes affine transformation parameter prediction to standardize already captured X-ray images into a specific composition. Additionally, we introduce a region-specific abnormality detection method that requires affine-transformed chest X-ray images. Furthermore, we propose a method to enhance application efficiency and performance through feature map hard masking. The experimental results demonstrate that our proposed approach achieved a maximum AUROC (Area Under the Receiver Operating Characteristic) of 0.774. Compared to a previous study conducted on the same dataset, our method shows a 6.9% higher performance and improved accuracy.