• 한국수학교육학회지시리즈E:수학교육논문집
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• 제23권3호
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• pp.923-951
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• 2009

중학교 수학 평가에서 지필평가가 차지하는 비율은 대부분의 학교에서 80% 이상이나, 지필평가의 분석은 거의 이루어지지 않고 있다. 이 논문에서는 중학교에서 실시한 이차방정식과 이차함수 영역에 대한 지필고사 문제들을 우리나라 교육과정의 수학교과 총괄목표 및 각 단원의 평가목표에 따라 분석한다.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 추계학술대회
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• pp.410-412
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• 2021

본 논문은 객체와 배경 히스토그램을 활용한 개선된 보행자 검출 방식을 제안하고 있다. HOG & SVM 알고리즘을 통해 검출한 객체는 사각형 형태로 검출된다. 사각형 영역 안에는 배경과 객체의 영역이 혼합되어있다. 배경을 제외한 객체의 영역만을 검출한다면 객체 관련 다양한 정보를 쉽게 얻을 수 있다. 검출된 사각형의 크기를 객체의 크기에 맞게 x-y축 투영 알고리즘을 사용하여 재조정한다. 그리고 나서 재조정 된 사각형 내의 객체에 대한 히스토그램을 바탕으로 배경과 객체를 구분하여 개선된 객체를 검출한다. 검출한 객체와 원본의 객체를 비교하는 신뢰성 평가인 정밀도와 재현율의 평균값이 각각 97.9%와 90%를 보이고 있다.

• Annals of Clinical Neurophysiology
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• 제25권2호
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• pp.55-65
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• 2023

The ultimate role of ocular movements is to keep the image of an object within the fovea and thereby prevent image slippage on the retina. Accurate evaluations of eye movements provide very useful information for understanding the functions of the oculomotor system and determining abnormalities therein. Such evaluations also play an important role in enabling accurate diagnoses by identifying the location of lesions and discriminating from other diseases. There are various types of ocular movements, and this article focuses on saccades, fast eye movements, smooth pursuit, and slow eye movements, which are the most important types of eye movements used in evaluations performed in clinical practice.

• 한국농공학회지
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• 제44권1호
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• pp.57-68
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• 2002

In the irrigation facilities, the irrigation system is connected systematically, and thus, it agrees to the object-oriented concept. Since it is necessary to go through comparative evaluations and to devise several alternatives plans in designing the irrigation system, it will be very efficient to use the objects that contain the design data. In this study, the object-oriented methodology has been proposed to define the objects, which will be used in the design system of irrigation facility. Furthermore, as for the essential elements of the objects, concept of element objects is formulated. By employing this concept, appropriate element objects have been derided for the irrigation facility. Necessary data model for realization of the objects is examined and selected. And then, required elements for applying the selected data model to the irrigation facility will be proposed

• ETRI Journal
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• 제45권5호
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• pp.811-821
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• 2023

We propose an adaptive unmanned aerial vehicle (UAV)-assisted object recognition algorithm for urban surveillance scenarios. For UAV-assisted surveillance, UAVs are equipped with learning-based object recognition models and can collect surveillance image data. However, owing to the limitations of UAVs regarding power and computational resources, adaptive control must be performed accordingly. Therefore, we introduce a self-adaptive control strategy to maximize the time-averaged recognition performance subject to stability through a formulation based on Lyapunov optimization. Results from performance evaluations on real-world data demonstrate that the proposed algorithm achieves the desired performance improvements.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제16권2호
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• pp.104-110
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• 2016

Dense local image descriptors like SIFT are fruitful for capturing salient information about image, shown to be successful in various image-related tasks when formed in bag-of-words representation (i.e., histograms). In this paper we consider to utilize these dense local descriptors in the object tracking problem. A notable aspect of our tracker is that instead of adopting a point estimate for the target model, we account for uncertainty in data noise and model incompleteness by maintaining a distribution over plausible candidate models within the Bayesian framework. The target model is also updated adaptively by the principled Bayesian posterior inference, which admits a closed form within our Dirichlet prior modeling. With empirical evaluations on some video datasets, the proposed method is shown to yield more accurate tracking than baseline histogram-based trackers with the same types of features, often being superior to the appearance-based (visual) trackers.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권5호
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• pp.2346-2362
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• 2016

As one of the most important issues in computer vision and image processing, online object tracking plays a key role in numerous areas of research and in many real applications. In this study, we present a novel tracking method based on the proposed structured sparse representation model, in which the tracked object is assumed to be sparsely represented by a set of object and background templates. The contributions of this work are threefold. First, the structure information of all the candidate samples is utilized by a joint sparse representation model, where the representation coefficients of these candidates are promoted to share the same sparse patterns. This representation model can be effectively solved by the simultaneous orthogonal matching pursuit method. In addition, we develop a tracking algorithm based on the proposed representation model, a discriminative candidate selection scheme, and a simple model updating method. Finally, we conduct numerous experiments on several challenging video clips to evaluate the proposed tracker in comparison with various state-of-the-art tracking algorithms. Both qualitative and quantitative evaluations on a number of challenging video clips show that our tracker achieves better performance than the other state-of-the-art methods.

• International journal of advanced smart convergence
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• 제12권4호
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• pp.182-189
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• 2023

A recently research, object detection and segmentation have emerged as crucial technologies widely utilized in various fields such as autonomous driving systems, surveillance and image editing. This paper proposes a program that utilizes the QT framework to perform real-time object detection and precise instance segmentation by integrating YOLO(You Only Look Once) and Mask R CNN. This system provides users with a diverse image editing environment, offering features such as selecting specific modes, drawing masks, inspecting detailed image information and employing various image processing techniques, including those based on deep learning. The program advantage the efficiency of YOLO to enable fast and accurate object detection, providing information about bounding boxes. Additionally, it performs precise segmentation using the functionalities of Mask R CNN, allowing users to accurately distinguish and edit objects within images. The QT interface ensures an intuitive and user-friendly environment for program control and enhancing accessibility. Through experiments and evaluations, our proposed system has been demonstrated to be effective in various scenarios. This program provides convenience and powerful image processing and editing capabilities to both beginners and experts, smoothly integrating computer vision technology. This paper contributes to the growth of the computer vision application field and showing the potential to integrate various image processing algorithms on a user-friendly platform

• Korean Journal of Geomatics
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• 제4권1호
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• pp.31-37
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• 2004

The aim of this research is comparing the existing approximation models (e.g. Affine Transformation and Direct Linear Transformation) with Rational Function Model as a substitute of rigorous sensor model of linear array scanner, especially push-broom sensor. To do so, this research investigates the mathematical model of each approximation method. This is followed by the assessments of accuracy of transformation from object space to image space by using simulated data generated by collinearity equations which incorporate or depict the physical aspects of linear array sensor.

• Journal of Multimedia Information System
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• 제4권2호
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• pp.89-92
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• 2017

This paper investigates simple gray level image enhancement technique based on Genetic Algorithms and Local Statistics. The task of GA is to adapt the parameters of local sliding masks over pixels, finding out the best parameters preserving the brightness and possibly preventing the creation of intensity artifacts in the local area of images. The algorithm is controlled by GA as to enhance the contrast and details in the images automatically according to an object fitness criterion. Results obtained in terms of subjective and objective evaluations, show the plausibility of the method suggested here.