• Korean Journal of Veterinary Research
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• v.22 no.1
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• pp.31-36
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• 1982

This study was taken to clarify the clinical signs and macroscopical lesions of pigs naturally infected with hog cholera. The clinical and macroscopical observation on the natural cases of hog cholera and experimental cases inoculated with ALD Virus and isolated virus strains were carried out. The results obtained are as follow; In clinical inspection of the natural cases, diarrhea (73.1%) blotching of ear (50.0%), staggering (42.3%), erythema of skin (40.0%), constipation (38.5%), conjunctivitis (32.7%) and dyspnea (30.8%) were observed. Dyspnea, constipation and erythema of skin were observed mainly in the experimental cases, however, staggering and conjunctivitis in pigs infected with ALD virus were found and convulsion and hemorrhage of skin of pigs infected with isolated virus were seen, respectively. The gross lesions of natural cases were hemorrhage of lymph node (82.5%), enteritis and hemorrhage of large intestine (65.0%), splenic infarction (57.5%), pneumonia (55.0%), gastritis and hemorrhage (52.5%), cardiac hemorrhage (40.0%) and renal petechiation (37.5%), while in the experimental cases, hemorrhage of lymph node, pneumonia, gastritis and hemorrhage, enteritis and hemorrhage of laryge intestine and splenic infarction were seen mainly.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.06a
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• pp.345-346
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• 2018

차종 별 교통량 자료는 도로의 유지관리나 분석 등의 행정 처리 업무에 필요한 기본 자료임과 동시에 각종 연구에 활용된다. 본 시스템은 그 일환으로서 화물차나 일반차량을 구분하여 특정 도로의 화물차 비율이나 교통량을 파악하는데 활용할 수 있다. 머신 러닝 알고리즘 중에서 높은 성능을 보이는 Support Vector Machine (SVM) 알고리즘을 이용하여 도로 위의 일반차량과 화물차를 구분하였다. 우선, 화물차와 일반차량의 차이를 구분하고자 각각의 영상에 대해 Histogram of Oriented Gradients (HOG) 기반 특징점을 추출하고 이에 따라 1 차원 벡터로 표현된 데이터를 SVM 으로 분류하여 구분한다.

• Korean Journal of Veterinary Service
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• v.25 no.1
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• pp.9-14
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• 2002

This survey was conducted to evaluate the microbiological quality and to detect of pathogenic microorganisms on the surface of slaughtered beef and pork products in two abattoirs located in Seoul from January 2001 through December 2001. Two hundred and twenty-five beef and 215 hog were surveyed for microbiological quality and 630 beef and 625 hog were detected for pathogenic microorgainsms. 1. The prevalence level on number of standard plate count(SPC) less than $10^4$cfu/$cm^2$in beef and hog were 89.8% and 90.7%, respectively. 2. Escherichia coli less than $10^2$cfu/$cm^2$ in beef and less than $10^3$cfu/$cm^2$ in hog were 98.2% and 99% 3. E coli 0157:H7 was recovered from 2 beef carcasses(0.32%), and Staphylococcus aureus from 12 pork carcasses(1.90%), Listeria monocytogenes from 1 beef and 4 pork carcasses (0.15%, 0.64%) and clostridium perfringens from 14 beef and 11 pork carcasses(2.22%, 1.76%), respectively.

• Journal of the Korea Institute of Military Science and Technology
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• v.20 no.1
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• pp.33-39
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• 2017

In this paper, an effective feature which is capable of classifying targets among the detections obtained from 2D range-bearing maps generated in active sonar environments is proposed. Most conventional approaches for target classification with the 2D maps have considered magnitude of peak and statistical features of the area surrounding the peak. To improve the classification performance, HOG(Histogram of Gradient) feature, which is popular for their robustness in the image textures analysis is applied. In order to classify the target signal, SVM(Support Vector Machine) method with reduced HOG feature by the PCA(Principal Component Analysis) algorithm is incorporated. The various simulations are conducted with the real clutter signal data and the synthesized target signal data. According to the simulated results, the proposed method considering HOG feature is claimed to be effective when classifying the active sonar target compared to the conventional methods.

• International Journal of Contents
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• v.9 no.3
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• pp.1-9
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• 2013

In this paper, we propose a fast and accurate system for detecting pedestrians from a static image. Histogram of Oriented Gradients (HOG) is a well-known feature for pedestrian detection systems but extracting HOG is expensive due to its high dimensional vector. It will cause long processing time and large memory consumption in case of making a pedestrian detection system on high resolution image or video. In order to deal with this problem, we use Principal Components Analysis (PCA) technique to reduce the dimensionality of HOG. The output of PCA will be input for a linear SVM classifier for learning and testing. The experiment results showed that our proposed method reduces processing time but still maintains the similar detection rate. We got twenty five times faster than original HOG feature.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.7
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• pp.996-1003
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• 2022

In this paper, we present a new method for determining the scan line and range for vision-based 1-D barcode recognition. This is a study on how to detect valid barcode representative points and directions by applying the DBSCAN clustering method based on block HOG (histogram of gradient) and determine scan lines and barcode crosslines based on this. In this paper, the minimum and maximum search techniques were applied to determine the cross-line range of barcodes based on the obtained scan lines. This can be applied regardless of the barcode size. This technique enables barcode recognition even by detecting only a partial area of the barcode, and does not require rotation to read the code after detecting the barcode area. In addition, it is possible to detect barcodes of various sizes. Various experimental results are presented to evaluate the performance of the proposed technique in this paper.

• Journal of IKEEE
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• v.18 no.1
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• pp.106-113
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• 2014

A pedestrian detector can be applied for various purposes such as monitoring or counting the number of people in some place, or detecting the people plunging in the driveway. There was a lot of related research. But, the detection speed is slow in embedded system because of the limited computing power. An algorithm for fast pedestrian detector using HOG in ARM SIMD architecture is presented in this paper. There is a way to quickly remove the background of image and to improve the detection speed using NEON parallel technique. When we tested with INRIA Person Dataset, the proposed pedestrian detector improves the speed by 3.01 times than previous one.

• Journal of Multimedia Information System
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• v.4 no.1
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• pp.33-38
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• 2017

This article suggests a new algorithm for detecting two-wheelers on the road that have various shapes according to viewpoints. Because of complicated shapes, it is more difficult than detecting a human. In general, the Histograms of Oriented Gradients(HOG) feature is well known as a useful method of detecting a standing human. We propose a method of detecting a human on a two-wheelers using the spatial relocation of HOG (Histogram of Oriented Gradients) features. And this paper adapted the contrast method which is generally using in the image process to improve the detection rate. Our experimental results show that a two-wheelers detection system based on proposed approach leads to higher detection accuracy, less computation, and similar detection time than traditional features.

• Korean Journal of Veterinary Research
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• v.6 no.1
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• pp.31-36
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• 1966

The free amino acid contents in several tissues of swine were analyzed qualitatively by means of two dimentional paper chromatography. The tissues used were liver, kidney and spleen that were obtained from normal, immunized and hog cholera infected swines. The results obtained are as follows: 1. Liver: 20 amino acids were detected in normal, 17 in immunized and 15 in infected swines. 2. Kidney: 16 amino acids were detected in normal, 13 in immunized and infected swines. 3. Spleen: 15 amino acids were detected in normal in immunized and 13 in infected swines. 4. Glutamic acid, leucine, serine and threonine were present in high concentration in all of the cases examined. 5. The free amino acids were appeard to be decreased in the infected tissues with hog cholera virus.

• Journal of Broadcast Engineering
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• v.21 no.1
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• pp.87-96
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• 2016

Recently, there is a need for automatic recognition of a variety of symbols on roads because of activation of information services using digital maps on the Web or mobile devices. This paper proposes a method which automatically recognizes 11 kinds of symbolic road markings on the road surface with HOG-SP(Histogram of oriented Gradients-Split Projection) descriptor and shows improvement of lane position detection with recognized symbolic road markings. With the proposed method, recognition rate of 81.99% has been proven on NAVER road view images and the experiments proves the superiority of proposed method by comparisons with other existing methods. Moreover, this paper shows 7.64% higher lane position detection rate by recognizing road surface marking beforehand than only detecting lanes' positions.