• ETRI Journal
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• v.39 no.5
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• pp.652-661
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• 2017

A mention has a noun or noun phrase as its head and constructs a chunk that defines any meaning, including a modifier. Mention detection refers to the extraction of mentions from a document. In mentions, coreference resolution refers to determining any mentions that have the same meaning. Pointer networks, which are models based on a recurrent neural network encoder-decoder, outputs a list of elements corresponding to an input sequence. In this paper, we propose mention detection using pointer networks. This approach can solve the problem of overlapped mention detection, which cannot be solved by a sequence labeling approach. The experimental results show that the performance of the proposed mention detection approach is F1 of 80.75%, which is 8% higher than rule-based mention detection, and the performance of the coreference resolution has a CoNLL F1 of 56.67% (mention boundary), which is 7.68% higher than coreference resolution using rule-based mention detection.

• Journal of KIISE
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• v.44 no.8
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• pp.774-781
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• 2017

Mention detection systems use nouns or noun phrases as a head and construct a chunk of text that defines any meaning, including a modifier. The term "mention detection" relates to the extraction of mentions in a document. In the mentions, a coreference resolution pertains to finding out if various mentions have the same meaning to each other. A pointer network is a model based on a recurrent neural network (RNN) encoder-decoder, and outputs a list of elements that correspond to input sequence. In this paper, we propose the use of mention detection using pointer networks. Our proposed model can solve the problem of overlapped mention detection, an issue that could not be solved by sequence labeling when applying the pointer network to the mention detection. As a result of this experiment, performance of the proposed mention detection model showed an F1 of 80.07%, a 7.65%p higher than rule-based mention detection; a co-reference resolution performance using this mention detection model showed a CoNLL F1 of 52.67% (mention boundary), and a CoNLL F1 of 60.11% (head boundary) that is high, 7.68%p, or 1.5%p more than coreference resolution using rule-based mention detection.

• Journal of Digital Convergence
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• v.10 no.2
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• pp.211-216
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• 2012

There are two kinks of processes could detect the laser pointer. One is the process which detects the location of the pointer. the other one is a possibility of dividing with the process which converts the coordinate of the laser pointer which is input in coordinate of the monitor. The previous Mean-Shift algorithm is not appropriately for real-time video image to calculate many quantity. In this paper, we proposed the context driven real-time laser pointer detection and tracking. The proposed method is a possibility of getting the result which is fixed from the situation which the background and the background which are complicated dynamically move. In the actual environment, we can get to give constant results when the object come in, when going out at forecast boundary. Ultimately, this paper suggests empirical application to verify the adequacy and the validity with the proposed method. Accordingly, the accuracy and the quality of image recognition will be improved the surveillance system.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.1
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• pp.21-30
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• 2011

In this paper, an effective method to detect the laser pointer on the screen using the neural network algorithm for implementing the human-computer interaction system. The proposed neural network algorithm is used to train the patches without a laser pointer from the input camera images, the trained neural network then generates output values for an input patch from a camera image. If a small variation is perceived in the input camera image, amplify the small variations and detect the laser pointer spot in the camera image. The proposed system consists of a laser pointer, low-price web-camera and image processing program and has a detection capability of laser spot even if the background of computer monitor has a similar color with the laser pointer spot. Therefore, the proposed technique will be contributed to improve the performance of human-computer interaction system.

• The KIPS Transactions:PartD
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• v.18D no.1
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• pp.35-44
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• 2011

Memory errors can cause not only program malfunctions but also even unexpected system halt. Though a programmer checks memory errors, some memory errors with low occurrence frequency are missed to detect. In this paper, we propose a method for effectively detecting such memory errors using instruction transition diagrams through analyzing assembly codes obtained by disassembling an executable file. Out of various memory errors, local memory return errors, null pointer access errors and uninitialized pointer access errors are targeted for detection. When applying the proposed method to various programs including well-known open source programs such as Apache web server and PHP script interpreter, some potential memory errors are detected.

• Journal of Sensor Science and Technology
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• v.27 no.4
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• pp.216-220
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• 2018

In this paper, we present visual sensing techniques that can be used to teach a robot using a laser pointer. The light spot of an off-the-shelf laser pointer is detected and its movement is tracked on consecutive images of a camera. The three-dimensional position of the spot is calculated using stereo cameras. The light spot on the image is detected based on its color, brightness, and shape. The detection results in a binary image, and morphological processing steps are performed on the image to refine the detection. The movement of the laser spot is measured using two methods. The first is a simple method of specifying the region of interest (ROI) centered at the current location of the light spot and finding the spot within the ROI on the next image. It is assumed that the movement of the spot is not large on two consecutive images. The second method is using a Kalman filter, which has been widely employed in trajectory estimation problems. In our simulation study of various cases, Kalman filtering shows better results mostly. However, there is a problem of fitting the system model of the filter to the pattern of the spot movement.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.2
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• pp.253-266
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• 2023

The Null Pointer Dereference vulnerability is a significant vulnerability that can cause severe attacks such as denial-of-service. Previous research has proposed methods for detecting vulnerabilities, but large and complex programs pose a challenge to their efficiency. In this paper, we present a lightweight tool for detecting specific functions in large binaryprograms through symbolizing variables and emulating program execution. The tool detects vulnerabilities through data dependency analysis and heuristics in each execution path. While our tool had an 8% higher false positive rate than the bap_toolkit, it detected all existing vulnerabilities in our dataset.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.938-941
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• 2010

Though a compiler checks memory errors, it is difficult for the compiler to detect function pointer errors in code level. Thus, in this paper, we propose a method for effectively detecting Invalid function pointer access errors, by analyzing assembly codes that are obtained by disassembling an executable file. To detect the errors, assembly codes in disassembled files are checked out based on the instruction transition diagrams which are constructed through analyzing normal usage patterns of function pointer access. When applying the proposed method to various programs having no compilation error, a total of about 500 potential errors including the ones of well-known open source programs such as Apache web server and PHP script interpreter are detected among 1 million lines of assembly codes corresponding to a total of about 10 thousand functions.

• Journal of the Korea Society of Computer and Information
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• v.12 no.6
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• pp.69-76
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• 2007

The main stream of presentation is interrupted because of the direct manipulation of their PC frequently so as to control the screen and file open and so on. A variety of products have been developed to solve these inconveniences of the conventional laser beam pointer [LBP] by simply adding a mouse function to the previous LBP. However. the LBPs fully supporting a mouse function are not yet appeared. In this paper. we developed the LBP fully fulfilling a mouse function using mono-camera as well as a robust image processing and analyzed the position detection accuracy. Finally we verified the developed LBP does not only fulfill a mouse function but also solve the defects of the current laser pointer such as inconvenient installation and Position detection errors due to the illumination and viewing direction changes.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.617-620
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• 2010

최근 고성능 모바일 단말기와 다양한 컨텐츠가 등장하면서 유비쿼터스 환경에서의 사용자 인터페이스에 대한 관심이 높아지고 있다. 특히 모바일 프로젝터는 장소의 제한을 받지 않고 큰 화면을 다른 사람과 공유할 수 있는 장점이 있는 반면에 단말기를 직접 제어해야 하는 불편함이 있다. 본 논문에서는 모바일 환경에서 카메라를 통해 입력된 영상 정보만으로 사용자가 스크린에 비추는 레이저 포인터를 실시간으로 검출하는 알고리즘을 제안한다. 제안하는 알고리즘은 색상 감지와 움직임 감지로 나뉜다. 단일 프레임에서 영상 성분의 평균을 이용한 조건을 검사하여 레이저 포인터 색상 영역을 검출하고, 인접한 프레임과 현재 프레임과의 차를 구하며 그 차이가 임계값보다 큰 영역을 움직임 영역으로 검출한다. 마지막으로 색상 검출 영역과 움직임 검출 영역을 동시에 만족하는 영역을 최종적으로 레이저 포인터 영역으로 인식한다. 본 기법은 영상 정보만 사용하기 때문에 센서나 불필요한 장비를 착용할 필요가 없고 영상 성분 평균을 이용하므로 프로젝터 성능에 따른 조도의 변화에 강건하여 효과적인 레이저 포인터 검출이 가능하다. 실험결과는 주변 조명의 밝기에 따라 차이가 있지만 대부분 80% 이상의 검출률과 16% 미만의 오검출률의 성능으로 나타났고, 이 같은 결과는 사용자의 주관적인 만족을 보장하였다.