• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.7
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• pp.816-822
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• 2016

Content-Based image retrieval is a method to search by image features such as local color, texture, and other image content information, which is different from conventional tag or labeled text-based searching. In real life data, the number of images having tags or labels is relatively small, so it is hard to search the relevant images with text-based approach. Existing image search method only based on image feature similarity has limited performance and does not ensure that the results are what the user expected. In this study, we propose and validate a machine learning based approach to improve the performance of the image search engine. We note that when users search relevant images with a query image, they would expect the retrieved images belong to the same category as that of the query. Image classification method is combined with the traditional image feature similarity method. The proposed method is extensively validated on a public PASCAL VOC dataset consisting of 11,530 images from 20 categories.

• Journal of Information Processing Systems
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• v.7 no.3
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• pp.447-458
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• 2011

This study presents a comprehensive solution to the collection management, which is based on the model for Cultural Objects (CCO). The developed system manages and spreads the collections that are safeguarded in museums and galleries more easily by using IT. In particular, we present our approach for a non-structured search and recovery of the objects based on the annotation of artwork images. In this methodology, we have introduced a faceted search used as a framework for multi-classification and for exploring/browsing complex information bases in a guided, yet unconstrained way, through a visual interface.

• Korean Journal of Soil Science and Fertilizer
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• v.50 no.6
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• pp.520-529
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• 2017

In Korea, the largest agricultural lands are paddy fields which have poor infiltration and drainage properties. Recently, Korean government pursuits cultivating upland crops in paddy fields to reduce overproduced rice in Korea. In order to succeed this policy, it is critical to set criteria suitability classification for upland crops cultivating in paddy field soils. The objective of this study was developing guideline of suitability classification for sesame cultivation in paddy field soils. Yields of sesame cultivated in paddy field soils and soil properties were investigated at 40 locations at nationwide scale. Soil properties such as topography, soil texture, soil moisture contents, slope, and drainage level were investigated. The guideline of suitability classification for sesame was determined by multi-regression method. As a result, sesame yields had the greatest correlation with topography, soil moisture content, and slope. Since sesame is sensitive to excessive soil moisture content, paddy fields with well drained, slope of 7-15% and mountain foot or hill were best suit for cultivating sesame. Sesame yields were greater with less soil moisture contents. Based on these results, area of best suitable paddy field land for sesame was 161,400 ha, suitable land was 62,600 ha, possible land was 331,600 ha, and low productive land was 1,075,500 ha. Compared to existing suitability classification, the new guideline of classification recommended smaller area of best or suitable areas to cultivate sesame. This result may suggest that sesame cultivation in paddy field can be very susceptible to soil moisture contents.

• Korean Journal of Remote Sensing
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• v.34 no.1
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• pp.141-150
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• 2018

Crop type classification is essential for supporting agricultural decisions and resource monitoring. Remote sensing techniques, especially using hyperspectral imagery, have been effective in agricultural applications. Hyperspectral imagery acquires contiguous and narrow spectral bands in a wide range. However, large dimensionality results in unreliable estimates of classifiers and high computational burdens. Therefore, reducing the dimensionality of hyperspectral imagery is necessary. In this study, the Random Forest (RF) classifier was utilized for dimensionality reduction as well as classification purpose. RF is an ensemble-learning algorithm created based on the Classification and Regression Tree (CART), which has gained attention due to its high classification accuracy and fast processing speed. The RF performance for crop classification with airborne hyperspectral imagery was assessed. The study area was the cultivated area in Chogye-myeon, Habcheon-gun, Gyeongsangnam-do, South Korea, where the main crops are garlic, onion, and wheat. Parameter optimization was conducted to maximize the classification accuracy. Then, the dimensionality reduction was conducted based on RF variable importance. The result shows that using the selected bands presents an excellent classification accuracy without using whole datasets. Moreover, a majority of selected bands are concentrated on visible (VIS) region, especially region related to chlorophyll content. Therefore, it can be inferred that the phenological status after the mature stage influences red-edge spectral reflectance.

• Fashion & Textile Research Journal
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• v.22 no.3
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• pp.310-322
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• 2020

This study investigated the classification and characteristics of augmented reality (AR) content of fashion brands. The AR contents of fashion brands were classified according to user participation space and content delivery method. Based on these types, eight case studies were conducted, along with a discussion of AR characteristics in terms of presence, interactivity, and immersion. The results showed that AR content could be divided into four types: offline visit-external information type, offline visit-internal experience type, online utilization-external information type, and online utilization-internal experience type. It was also found that there were differences in characteristics for each type of AR content. First, the offline visit-external information type requires various new content that can provide entertainment immersion to users. Second, the offline visit-internal experience type requires a powerful inducement for users to visit a specific space providing AR content and to participate in augmented environments. Third, the online utilization-external information type needs a series of AR content that can consistently incite users' curiosity about brands and products. Fourth, the online utilization-internal experience type needs effective content to improve users' shopping experience with the virtual fitting of fashion accessories, such as eyewear, hats, jewelry, and watches. Accordingly, fashion companies should create contents that can provide appropriate presence, interactivity, and immersion by AR type.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1445-1456
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• 2003

The ASTER TIR (thermal infrared radiometer) sensor has 5 spectral bands over 8 to 12 ${\mu}$m region. Rock type classification using the ASTER TIR nighttime data was performed in the Erta Ale range of the Ethiopian Rift Valley. Erta Ale range is the most important axial volcanic chain of the Afar region. The petrographic diversity of lava erupted in this area is very important, ranging from magnesian transitional basalt to rhyolites. We tried to classify the rock types based on the spectral behavior of each volcanic rock types in thermal infrared range and estimated SiO$_{2}$ content with emission data by the ASTER TIR.

• The Journal of the Korea Contents Association
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• v.19 no.11
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• pp.499-506
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• 2019

Virtual reality, which is attracting attention due to the 4th Industrial Revolution and commercialization of 5G technology, is expanding its scope from gaming to tourism, leisure, and education, and the VR market is expected to expand continuously. As the VR market scales up in Korea, theme parks combining virtual reality contents are spreading around the city center. Unlike the existing theme parks, VR Theme Park is a small amusement culture space that is organized indoors, and you can enjoy attractions (ride) that can be enjoyed in an amusement park with virtual reality contents. Virtual reality content, which has the same characteristics as a theme park whose purpose is to experience extraordinary experiences, provides high immersion and presence in combination with the physical stimulus of attraction. The virtual reality content combined with the attraction cannot be classified accurately with the existing classification method, so a new classification method is proposed according to the experience type and the installation type. The contents were categorized through the case of the domestic VR theme park, and the planning direction for the creation of the virtual reality attraction contents that was going on was sought.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.10C
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• pp.1000-1009
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• 2007

This paper presents a content adaptive interpolation (CAI) for intra deinterlacing. The CAI consists of three steps: pre-processing, content classification, and adaptive interpolation. There are also three main interpolation methods in our proposed CAI, i.e. modified edge-based line averaging (M-ELA), gradient directed interpolation (GDI), and window matching method (WMM). Each proposed method shows different performances according to spatial local features. Therefore, we analyze the local region feature using the gradient detection and classify each missing pixel into four categories. And then, based on the classification result, a different do-interlacing algorithm is activated in order to obtain the best performance. Experimental results demonstrate that the CAI method performs better than previous techniques.

• The Journal of the Korea Contents Association
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• v.9 no.3
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• pp.108-117
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• 2009

Current mobile content's classifications have two major problems. One violates a principle of classification and the other reveals limitations in dealing with various convergence services. This study proposes a new mobile content's classification system to resolve these problems by adapting Al Ries's principle of symmetric and asymmetric transition. Symmetric mobile contents take a form of mutation in convergence process; therefore, the contents would appear different from their originals whereas asymmetric type combines mobile contents in an autonomous way. This new system not only demonstrates a clearer classification but also implies the trend of mobile content development and services. The current suggests that symmetric type is preferable and symmetric type of mobile contents is re-developed to become a symmetric type as much as the technology can support. Nonetheless, it is found that asymmetric type would still be serviced to some extent. Thus, new mobile content's classification, proposed in this research, provides a more constructive understating of mobile content's directions in the era of digital convergence and a ground for comparative analysis of mobile content's development or positioning strategies.

• Journal of Korean Clinical Nursing Research
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• v.18 no.3
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• pp.354-367
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• 2012

Purpose: This study was done to verify validity and reliability of a neonatal patient classification system (NeoPCS-1). Methods: An expert group of 8 nurse managers and 40 nurses from 8 Neonatal Intensive Care Units in Korea, verified content validity of the measurement using item level content validity index (I-CVI). The participants were nurses caring for 469 neonates. Data were collected from November 11 to December 14, 2011 and analyzed using descriptive statistics, ANOVA, intraclass correlation coefficient, and K-cluster analysis with PASW 18.0 program. Results: Nursing domains and activities included 8 items with 91 activities. I-CVI was above .80 in all areas. Interrater reliability was significant between two raters (r=.95, p<.001). Classification scores for participants according to patient types and nurses' intuition were significantly higher for the following patients; gestational age (${\leq}29$ weeks), body weight (<1,000 gm), and transfer from hospital. Six groups were classified using cluster analysis method based on nursing needs. Patient classification scores were significantly different for the groups. Conclusion: These results show adequate validity and reliability for the NeoPCS-1 based on nursing needs. Study is needed to refine the measurement and develop index scores to estimate number of nurses needed for adequate neonatal care.