• Journal of Broadcast Engineering
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• v.27 no.4
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• pp.538-547
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• 2022

Recently introduced image classification methods using Transformers show remarkable performance improvements over conventional neural network-based methods. In order to effectively consider regional features, research has been actively conducted on how to apply transformers by dividing image areas into multiple window areas, but learning of inter-window relationships is still insufficient. In this paper, to overcome this problem, we propose a transformer structure that can reflect the relationship between windows in learning. The proposed method computes the importance of each window region through compression and a fully connected layer based on self-attention operations for each window region. The calculated importance is scaled to each window area as a learned weight of the relationship between the window areas to re-calibrate the feature value. Experimental results show that the proposed method can effectively improve the performance of existing transformer-based methods.

• Proceedings of the KSME Conference
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• 2008.11b
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• pp.2070-2075
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• 2008

Identification of steady-state is the first step in developing a fault detection and diagnosis (FDD) system. In a complete FDD system, the steady-state detector will be included as a module in a self-learning algorithm which enables the working system's reference model to "tune" itself to its particular installation. In this study, a steady-state detector of a residential air conditioner based on moving windows was designed. Seven representing measurements were selected as key features for steady-state detection. The optimized moving window size and the feature thresholds was suggested through startup transient test and no-fault steady-state test. Performance of the steady-state detector was verified during indoor load change test. From the research, the general methodology to design a moving window steady-state detector was provided for vapor compression applications.

• Genomics & Informatics
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• v.17 no.1
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• pp.4.1-4.7
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• 2019

In this paper, we propose a window-based mechanism visualization approach as an alternative way to measure the seriousness of the difference among data-insights extracted from a composite biodata point. The approach is based on two components: undirected graph and Mosaab-metric space. The significant application of this approach is to visualize the segmented genome of a virus. We use Influenza and Ebola viruses as examples to demonstrate the robustness of this approach and to conduct comparisons. This approach can provide researchers with deep insights about information structures extracted from a segmented genome as a composite biodata point, and consequently, to capture the segmented genetic variations and diversity (variants) in composite data points.

• Journal of the Semiconductor & Display Technology
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• v.15 no.3
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• pp.1-5
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• 2016

In order to apply sub-resolution assist feature (SRAF) in extreme ultraviolet lithography, the maximum non-printing SRAF width and lithography process margin needs to be improved. Through simulation, we confirmed that the maximum SRAF width of 6% attenuated phase shift mask (PSM) is large compared to conventional binary intensity mask. The increase in SRAF width is due to dark region's reflectivity of PSM which consequently improves the process window. Furthermore, the critical dimension error caused by variation of SRAF width and center position is reduced by lower change in diffraction amplitude. Therefore, we speculate that the margin of SRAF application will be improved by using PSM.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.7
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• pp.1437-1446
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• 2012

In this paper we propose a new stereo matching algorithm which is suitable for application to obtain depth information with high-speed in stereoscopic camera environment. For satisfying these condition we propose a new adaptive stereo matching technique using frequency information in discrete wavelet (DWT) domain and variable matching window. The size of the matching window is selected by analysis of the local property of the image in spatial domain and the feature and scaling factor of the matching window is selected by the frequency property in the frequency domain. For using frequency information we use local DWT and global DWT. We identified that the proposed technique has better peak noise to signal ratio (PSNR) than the fixed matching techniques with similar complexity.

• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.628-631
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• 1988

This paper describes a fingerprint classification on the basis of feature points(whorl, core) and feature vector and uses a syntactic approach to identify the shape of flow line around the core. Fingerprint image is divided into 8 by 8 subregions and fingerprint region is separated from background. For each subregion of fingerprint region, the dominant ridge direction is obtained to use the slit window quantized in 8 direction and relaxation is performed to correct ridge direction code. Feature points(whorl, core, delta) are found from the ridge direction code. First classification procedure divides the types of fingerprint into 4 class based on whorl and cores. The shape of flow line around the core is obtained by tracing for the fingerprint which has one core or two core and is represented as string. If the string is acceptable by LR(1) parser, feature vector is obtained from feature points(whorl, core, delta) and the shape of flow line around the core. Feature vector is used hierarchically and linearly to classify fingerprint again. The experiment resulted in 97.3 percentages of sucessful classification for 71 fingerprint impressions.

• The Transactions of the Korea Information Processing Society
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• v.6 no.2
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• pp.543-551
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• 1999

The primary purposes in this paper are to analyze the class separation of features in handwritten numeral recognition and to make use of the results in feature selection. Using the Parzen window technique, we compute the class distributions and define the class separation to be the overlapping distance of two class distributions. The dimension of a feature vector is reduced by removing the void or redundant feature cells based on the class separation information. The experiments have been performed on the CENPARMI handwritten numeral database, and partial classification and full classification have been tested. The results show that the class separation is very effective for the feature selection in the 10-class handwritten numeral recognition problem since we could reduce the dimension of the original 256-dimensional feature vector by 22%.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.275-279
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• 2002

Change Detection is a useful technology that can be applied to various fields, taking temporal change information with the comparison and analysis among multi-temporal satellite images. Especially, Change Detection that utilizes high-resolution satellite imagery can be implemented to extract useful change information for many purposes, such as the environmental inspection, the circumstantial analysis of disaster damage, the inspection of illegal building, and the military use, which cannot be achieved by low- or middle-resolution satellite imagery. However, because of the special characteristics that result from high-resolution satellite imagery, it cannot use a pixel-based method that is used for low-resolution satellite imagery. Therefore, it must be used a feature-based algorithm based on the geographical and morphological feature. This paper presents the system that builds the change map by digitizing the boundary of the changed object. In this system, we can make the change map using manual or semi-automatic digitizing through the user interface implemented with a floating window that enables to detect the sign of the change, such as the construction or dismantlement, more efficiently.

• 한국정보디스플레이학회:학술대회논문집
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• 2005.07b
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• pp.1615-1618
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• 2005

In this paper, implementation of object-based multiview 3D display using object segmentation and adaptive disparity estimation is proposed and its performance is analyzed by comparison to that of the conventional disparity estimation algorithms. In the proposed algorithm, firstly we can get segmented objects by region growing from input stereoscopic image pair and then, in order to effectively synthesize the intermediate view the matching window size is selected according to the extracted feature value of the input stereo image pair. Also, the matching window size for the intermediate view reconstruction (IVR) is adaptively selected in accordance with the magnitude of the extracted feature value from the input stereo image pair. In addition, some experimental results on the IVR using the proposed algorithm is also discussed and compared with that of the conventional algorithms.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11b
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• pp.300-306
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• 2000

This paper introduces a new concept of automation for bio-production with tele-operative system. The proposed system showed practical and feasible way of automation for the volatile bio-production process. Based on the proposition, recognition of the job environment with object identification was performed using computer vision system. A man-machine interactive hybrid decision-making, which utilized a concept of tele-operation was proposed to overcome limitations of the capability of computer in image processing and feature extraction from the complex environment image. Identifying watermelons from the outdoor scene of the cultivation field was selected to realize the proposed concept. Identifying watermelon from the camera image of the outdoor cultivation field is very difficult because of the ambiguity among stems, leaves, shades, and especially fruits covered partly by leaves or stems. The analog signal of the outdoor image was captured and transmitted wireless to the host computer by R.F module. The localized window was formed from the outdoor image by pointing to the touch screen. And then a sequence of algorithms to identify the location and size of the watermelon was performed with the local window image. The effect of the light reflectance of fruits, stems, ground, and leaves were also investigated.