Rock classification is fundamental discipline of exploring geological and geotechnical features in a site, which, however, may not be easy works because of high diversity of rock shape and color according to its origin, geological history and so on. With the great success of convolutional neural networks (CNN) in many different image-based classification tasks, there has been increasing interest in taking advantage of CNN to classify geological material. In this study, a feasibility of the deep CNN is investigated for automatically and accurately identifying rock types, focusing on the condition of various shapes and colors even in the same rock type. It can be further developed to a mobile application for assisting geologist in classifying rocks in fieldwork. The structure of CNN model used in this study is based on a deep residual neural network (ResNet), which is an ultra-deep CNN using in object detection and classification. The proposed CNN was trained on 10 typical rock types with an overall accuracy of 84% on the test set. The result demonstrates that the proposed approach is not only able to classify rock type using images, but also represents an improvement as taking highly diverse rock image dataset as input.
The Journal of Korean Institute of Electromagnetic Engineering and Science
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v.21
no.4
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pp.408-416
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2010
A study on the calibration of an X-band HPS(Hongik Polarimetric Scatterometer) system for ground-based operation is presented in this paper. In order to calibrate the scatterometer system, the degree of its distortions are analyzed by comparison between theoretical- and measured-values using the theoretically well-known calibration targets such as a metal sphere, a trihedral corner reflector(CR) and a metal cylinder. The calibration works in the field conditions depend on the precise and stable measurements of those calibration target. we present a measurement technique, so-called, an automatic 2-D target-scanning technique, using the incidence-angle(${\xi}-$ and ${\phi}-$ directions) control of HPS system. Then, we used STCT(Single-Target Calibration Technique) and GCT(General Calibration Technique) to calibrate a distortion of the scatterometer system, and measured the polarimetric RCS(Radar Cross Section) and phase-difference of a trihedral-CR as a test-target to verify the accuracy of the calibration technique. Then, three different types(i.e., 10, 20, 30 cm) of trihedral-CR were used. we obtained the error ranges about ${\pm}1.0$dB, ${\pm}0.5$ dB in a polarimetric RCS and about $-20^{\circ}{\sim}0^{\circ}$ and ${\pm}5^{\circ}$ in the co-polarized phase-difference by using the GCT and STCT, respectively.
Kang, Dong Hyeon;Lee, Si Young;Kim, Jong Koo;Park, Min Jung;Son, Jin Kwan;Yun, Sung-Wook;An, Se Woong;Jung, In Kyu
Journal of Bio-Environment Control
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v.26
no.3
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pp.215-220
/
2017
This study was conducted to improve the insufficiency of fruit vegetable grafting system developed by National Institute of Agricultural Sciences, Rural Development Administration. When the rotary blade cut the stem of scions and rootstocks, the grafting failure at curved cutting surfaces happened. The cutting depth of a tomato seedling by a rotated cutter was calculated 0.11 mm even when the cutting arm length and the maximum stem diameter were 50 mm and 5 mm, respectively. Mathematical analysis and high-speed photography showed that there was no problem by cutting in straight the stem of scions and rootstocks. The compression test of seedling stems to design the optimal shape of gripper showed that stems were not completely restored when they were compressed above 0.8 mm and 0.6 mm in case of rootstocks and scion, respectively. This study found that the bending angle of stem of tomato seedlings at the grafting period was 10 degree on average. The optimal gripper finger was the edge finger type which could be precisely set center point by adjusting the distance between fingers. In addition, it was found that most of seedling could be grasped without damage when the finger-to-finger distances is set to 2.5 mm for scion and 3.0 mm for rootstocks and finger are coated by 1 mm-thick flexible material.
Structual ambiguity is one of those problem that arise in the analysis of natural language sentences.It has been considered very difficult to solve the problem.Structural ambiguity,however,should be resolved no matter how difficult it may be.Otherwise natural language processing could be virtually impossible.A statistical approach to structural disambiguation is proposed in this dissertation.The information-theoretic concept of mutual information has been empolyed in resolving structural ambiguity Mutual information can be acquired in an automatic way.from text corpora. If a structural disambiguation subsystem had the capability of self-evaluating whether the results of structural disambiguation are correct or not.it would be possible to develop a more intelligent natural language proessing system.In this paper,the concept of confidence measure is also proposed to endow the disambiguation subsystem with such intelligence.Confidence measure is a numeric value calculated after structural disambiguation. Some experiments were performed in order to show the validity of the approach.Mutual information was auto matically acquired from a corpus of 1.6milion words that were collected from scientific abstracts.The accuracy of structural disambiguation was 80%when performed over 1,639 test sentences.Notice that there was no manual tuning in advance for the experiments.The task of detecting and correcting errors in structural disambiguation will be performed very effectively if the concept of confidence measure is employed in the process.
Generally, it is known that the spleen accompanied by liver cirrhosis is hypertrophied or enlarged. We examined the wave pattern of the spleen by using abdominal CT images of a patient with liver cirrhosis, and found that they are different from those of a person with a normal liver In the abdominal CT image of the patient with liver cirrhosis, there is a deep wave part on the left side of the spleen. In the case of the normal liver, there are waves on the left side, but they aren't deep. Therefore, the total area of waving parts of the spleen with liver cirrhosis is found to be greater than that of the spleen with the normal liver. Moreover, when examining circularity by abstracting the waves of the spleen from the image iO liver cirrhosis, we found they are more circular than those of the spleen accompanied by a normal liver. This paper suggests an automatic method to diagnose splenic enlargement by using the wave pattern of the spleen in abdominal CT images on the basis of the two principles. It tells us that we can judge if the abdomen has a focal splenic enlargement automatically, without the manual test of the size of spleen, only with the shape of spleen.
Moving object boundary is very important for the accurate segmentation of moving object. We extract the moving object boundary from the moving object edge. But the object boundary shows broken boundaries so we develop a novel boundary linking algorithm to link the broken boundaries. The boundary linking algorithm forms a quadrant around the terminating pixel in the broken boundaries and searches for other terminating pixels to link in concentric circles clockwise within a search radius in the forward direction. The boundary linking algorithm guarantees the shortest distance linking. We register the background from the image sequence using the stationary background filtering. We construct two object masks, one object mask from the boundary linking and the other object mask from the initial moving object, and use these two complementary object masks to segment the moving objects. The main contribution of the proposed algorithms is the development of the novel object boundary linking algorithm for the accurate segmentation. We achieve the accurate segmentation of moving object, the segmentation of multiple moving objects, the segmentation of the object which has a hole within the object, the segmentation of thin objects, and the segmentation of moving objects in the complex background using the novel object boundary linking and the background automatically. We experiment the algorithms using standard MPEG-4 test video sequences and real video sequences of indoor and outdoor environments. The proposed algorithms are efficient and can process 70.20 QCIF frames per second and 19.7 CIF frames per second on the average on a Pentium-IV 3.4GHz personal computer for real-time object-based processing.
PURPOSES : This study aims to investigate the snow-melt effects of an underground electric heater's snow-melt system via a field performance test, for evaluating the suitability of the system for use on a concrete pavement. The study also investigates the effectiveness of dynamic measures for clearing snow after snowfall events. METHODS : In order to check the field applicability, in November 2010, specimens were prepared from materials used for constructing concrete pavements, and underground electric heating meshes (HOT-mesh) were buried at depths of 50 mm and 100 mm at the site of the Incheon International Airport Construction Research Institute. Further, an automatic heating control system, including a motion sensor and pavement-temperature-controlled sensor, were installed at the site; the former sensor was intended for determining snow-melt effects of the heating control system for different snowfall intensities. Pavement snow-melt effects on snowy days from December 2010 to January 2011 were examined by managing the electric heating meshes and the heating control system. In addition, data on pavement temperature changes resulting from the use of the heating meshes and heating control system and on the dependence of the correlation between the outdoor air temperature and the time taken for the required temperature rise on the depth of the heating meshes were collected and analyzed. RESULTS : The effects of the heating control system's preheat temperature and the hot meshes buried at depths of 50 mm and 100 mm on the melting of snow for snowfalls of different intensities have been verified. From the study of the time taken for the specimen's surface temperature to increase from the preheat temperature ($0^{\circ}C$) to the reference temperature ($5{\sim}8^{\circ}C$) for different snowfall intensities, the correlation between the burial depth and outdoor air temperature has been determined to be as follows: Time=15.10+1.141Depth-6.465Temp CONCLUSIONS : The following measures are suggested. For the effective use of the electric heating mesh, it should be located under a slab it may be put to practical use by positioning it under a slab. From the management aspect, the heating control system should be adjusted according to weather conditions, that is, the snowfall intensity.
Park, Hyonghu;Park, Jikoon;Choi, Ilhong;Kang, Sangsik;Noh, Sicheol;Jung, Bongjae
Journal of the Korean Society of Radiology
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v.9
no.6
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pp.369-374
/
2015
In this study we proposed a texture feature analysis algorithm that distinguishes between a normal image and a diseased image using CT images of some brain hemorrhage patients, and generates both Eigen images and test images which can be applied to the proposed computer aided diagnosis system in order to perform a quantitative analysis for 6 parameters. And through the analysis, we derived and evaluated the recognition rate of CT images of brain hemorrhage. As the results of examining over 40 example CT images of brain hemorrhage, the recognition rates representing a specific texture feature-value are as follows: some appeared to be as high as 100% including average gray level, average contrast, smoothness, and Skewness while others showed a little low disease recognition rate: 95% for uniformity and 87.5% for entropy. Consequently, based on this research result, if a software that enables a computer aided diagnosis system for medical images is developed, it will lead to the availability for the automatic detection of a diseased spot in CT images of brain hemorrhage and quantitative analysis. And they can be used as computer aided diagnosis data, resulting in the increased accuracy and the shortened time in the stage of final reading.
Purpose: The scan time reduction helps to yield more accurate results and induce the minimization of patient's motion. Also we can expect that satisfaction of examination will increase. Nowdays medical equipment companies have developed various programs to reduce scan time. We used Onco. Flash (Pixon method, SIEMENS) that is an image processing technique gated cardiac blood pool scan and going to evaluate its clinical usefullness. Materials and Method: We analyzed the 50 patients who were examined by gated blood pool scan in nuclear medicine department of Asan Mediacal Center from June $20^{th}$ 2008 to August $14^{th}$ 2008. We acquired the Full-time (6000 Kcounts) and Half-time (3000 Kcounts) LAO image in same position. And we acquired LVEF values ten times from Full-time, Half-time images acquired by the image processing technique and analyzed its mean and standard deviation values. To estimate LVEF in same conditions, we set automatic location of the LV ROI and background ROI based on same X and Y-axis. Also we performed blinding tests to physician. Results: After making a quantitative analysis of the 50 patients EF values, each mean${\pm}$standard deviation is shown at Full-time image $68.12{\pm}7.84%$, Half- time (acquired by imaging processing technique) $68.49{\pm}8.73%$. In the 95% confidence limit, there was no statistically significant difference (p>0.05). After blinding test with a physician for making a qualitative analysis, there was no difference between Full-time image and Half-time image acquired by the image processing technique for observing LV myocardial wall motion. Conclusion: Gated cardiac blood pool scan has been reported its relatively exact EF measured results than ultrasound or CT. But gated cardiac blood pool scan takes relatively longer time than other exams and now it needs to improve time competitive power. If we adapt Half-time technique to gated cardiac blood pool scintigraphy based on this study, we expect to reduce possible artifacts and improve accessibility as well as flexibility to exam. Also we expect patient's satisfaction.
Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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v.27
no.5
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pp.619-628
/
2009
LiDAR has capability of rapid data acquisition and provides useful information for reconstructing surface of the Earth. However, Extracting information from LiDAR data is not easy task because LiDAR data consist of irregularly distributed point clouds of 3D coordinates and lack of semantic and visual information. This thesis proposed methods for automatic extraction of buildings and 3D detail modeling using airborne LiDAR data. As for preprocessing, noise and unnecessary data were removed by iterative surface fitting and then classification of ground and non-ground data was performed by analyzing histogram. Footprints of the buildings were extracted by tracing points on the building boundaries. The refined footprints were obtained by regularization based on the building hypothesis. The accuracy of building footprints were evaluated by comparing with 1:1,000 digital vector maps. The horizontal RMSE was 0.56m for test areas. Finally, a method of 3D modeling of roof superstructure was developed. Statistical and geometric information of the LiDAR data on building roof were analyzed to segment data and to determine roof shape. The superstructures on the roof were modeled by 3D analytical functions that were derived by least square method. The accuracy of the 3D modeling was estimated using simulation data. The RMSEs were 0.91m, 1.43m, 1.85m and 1.97m for flat, sloped, arch and dome shapes, respectively. The methods developed in study show that the automation of 3D building modeling process was effectively performed.
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