• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.361-362
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• 2006

Magnetic Flux Leakage (MFL) inspection is a general non-destructive testing (NDT) method to detect the corrosion of natural gas pipelines. Currently, it is subjectively analyzed by trained analysts. In spite of investing much time and human resources, the inspection results may be different according to the analysts' expertise. So, many gas suppliers are keenly interested in the automation of the interpretation process. This paper presents a Gaussian variance filtering method of MFL signals, which is taken from MFL pigging of underground pipelines. In the proposed algorithm the original MFL signals are filtered by multiple Gaussians with different variance. Experimental results show that this approach does not need to align bias and to use explicit noise reduction algorithm.

• Korean Journal of Remote Sensing
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• v.20 no.3
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• pp.189-196
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• 2004

This paper describes what an operational change detection tool requires and the software which was designed and developed according to the requirements. The top requirement for the application of the software to operational change detection was identified: minimization of false detections, missing detections and operational cost. In order to meet such a requirement, the software was designed with the concept that the ultimate decision and isolation of changes must be performed manually by visual interpretation and all automatic algorithms and/or visualization techniques must be defined as support functions. In addition, the modular structure of the proposed software enables the addition of a new support function with the minimum development cost and minimum change of the operational environment.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1206-1208
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• 2003

The extraction of earthquake damage from remote sensed imagery requires high spatial resolution and temporal effectiveness of acquisition of imagery. The analog photographs and visual interpretation were taken traditionally. Now it is possible to acquire damage information from many commercial high resolution RS satellites. The key techniques are processing velocity and precision. The authors developed the automatic / semiautomatic image process techniques including feature enhancement, and classification, designed the emergency Earthquake Damage and Losses Evaluate System based on Remote Sensing (RSEDLES). The paper introduced the functions of RSEDLES as well as its application to the earthquakes occurred recently.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.124-131
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• 2024

Breast cancer classification using ultrasound, while widely employed, faces challenges due to its relatively low predictive value arising from significant overlap in characteristics between benign and malignant lesions, as well as operator-dependency. To alleviate these challenges and reduce dependency on radiologist interpretation, the implementation of automatic breast cancer classification in ultrasound image can be helpful. To deal with this problem, we propose a semi-supervised deep learning framework for breast cancer classification. In the proposed method, we could achieve reasonable performance utilizing less than 50% of the training data for supervised learning in comparison to when we utilized a 100% labeled dataset for training. Though it requires more modification, this methodology may be able to alleviate the time-consuming annotation burden on radiologists by reducing the number of annotation, contributing to a more efficient and effective breast cancer detection process in ultrasound images.

• The KIPS Transactions:PartB
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• v.10B no.4
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• pp.429-442
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• 2003

In this paper, we describe an address image recognition system for automatic processing of standard- size letter mail. The inputs to the system are gray-level mail piece images and the outputs are delivery point codes with which a delivery sequence of carrier can be generated. The system includes five main modules; destination address block location, text line separation, character segmentation, character recognition and finally address interpretation. The destination address block is extracted on the basis of experimental knowledge and the line separation and character segmentation is done through the analysis of connected components and vortical runs. For recognizing characters, we developed MLP-based recognizers and dynamical programming technique for interpretation. Since each module has been implemented in an independent way, the system has a benefit that the optimization of each module is relatively easy. We have done the experiment with live mail piece images directly sampled from mail sorting machine in Yuseong post office. The experimental results prove the feasibility of our system.

• Journal of Korea Multimedia Society
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• v.15 no.11
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• pp.1319-1329
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• 2012

AGVs are more and more utilized nowadays and magnetic guided AGVs are most widely used because their system has low cost and high speed. But this type of AGVs requires high infrastructure building cost and has poor flexibility of navigation path layout changing. Thus it is hard to applying this type of AGVs to a small quantity batch production system or a cooperative production system with many AGVs. In this paper, we propose a vision based guideline interpretation technique that uses the cheap, easily installable and changeable color tapes (or paint) as a guideline. So a vision-based AGV with color tapes is effectively applicable to the production systems. For easy setting and changing of AGV navigation path, we suggest an automatic method for interpreting a complex guideline layout including multi-branches and joins of branches. We also suggest a trace direction decision method for stable navigation of AGVs. Through several real-time navigation tests with an industrial AGV installed with the suggested technique, we confirmed that the technique is practically and stably applicable to real industrial field.

• Journal of Korean Society of Forest Science
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• v.96 no.3
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• pp.251-258
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• 2007

Airborne Lidar (light detection and ranging) can be an effective alternative in forest inventory to overcome the limitations of conventional field survey and aerial photo interpretation. In this study, we attempt to develop methodologies to identify individual trees and to estimate tree height from airborne Lidar data. Initially, digital elevation model (DEM) data representing the exact ground surface were generated by removing non-ground returns from the multiple-return laser point clouds, obtained over the coniferous forest site of rugged terrain. Based on the canopy height model (CHM) data representing non-ground layer, individual tree heights are extracted through pseudo-grid method and moving window filtering algorithm. Comparing with field survey data and aerial photo interpretation on sample plots, the number of trees extracted from Lidar data show over 90% accuracy and tree heights were underestimated within 1.1m in average at two plantation stands of pine (Pinus koraiensis) and larch (Larix leptolepis).

• Journal of Environmental Science International
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• v.19 no.6
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• pp.747-753
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• 2010

It follows in quality and sewage exclusion method of the investigation objective sector and the Combined Sewer Overflows which is suitable in regional characteristics and the confluence area against the rainfall initially a flow and the medulla and measurement - it analyzes the initial rainfall outflow possibility control plan which is suitable in the domestic actual condition and it proposes the monitor ring plan for the long-term flow and pollution load data accumulation. From the research which it sees the Infiltration water/Influent water and CSOs investigation it passes by the phase of hazard chain and Namwon right time 4 it does not hold reverse under selecting, Measurement it used the hazard automatic flow joint seal Sigma 910 machine and in case 15 minute interval of the I/I, it measured a flow at case 5, 15 minute standing of the CSOs. The water quality investigation for the water leakage investigation of the I/I and the sewage from the point which is identical with flow measurement during on-the-spot inspection duration against 6 items which include the BOD sampling and an analysis, when the rainfall analysis for CSOs fundamental investigation analyzed against 18 items which include the BOD sampling. Consequently, for the optimum interpretation invasion water / inflow water of the this investigation area day average the lowest flow - water quality assessment veterinarian optimum interpretation hazard average per day - lowest flow - it averages a medulla evaluation law department one lowest flow evaluation technique and it selects, it presentation collectively from here it gets, position result with base flow analysis of invasion water / inflow water.

• Economic and Environmental Geology
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• v.14 no.3
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• pp.193-201
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• 1981

The problem of automatic inversion of apparent resistivity sounding curves resulting from horizontally layered earth models is solved using the least-squares technique. This method, which makes use of damped least-squares algorithm in conjunction with digital filtering technique, is found to be speedier and more accurate than the conventional curve-matching method. Four sounding curves were chosen to test the inversion scheme. The analysis of the theoretical sounding data associated with a three-layer model illustrates clear advantages over the conventional curve-matching method. The usefulness of the inversion method is also shown when applied to the actual field data. It was found that the best fit earth models coincide with the subsurface structures confirmed by drilling.

• Geophysics and Geophysical Exploration
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• v.6 no.1
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• pp.7-12
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• 2003

The lineament extraction from satellite images is important in the geologic studies including groundwater and mineral exploration, groundwater survey, natural hazard analysis, and many others. The lineaments in remote sensing images are identified by the difference of pixel values or brightness. Since the visual interpretation is apt to be influenced by the knowledges and experiences, many of the automatic lineament detection algorithms are developed to ensure the objectives and efficient outputs. DSTA (dynamic segment tracing algorithm) is one of such algorithms, which can be applied to not only mountainous area but also alluvial area. However, when the alluvial area is wider than mountain region, somewhat severe noises are generated. To reduce such noises, AERA (alluvial effect reducing algorithm) is proposed and tested for the image which contains mountains, cultivated land and urban area. Upon the application of AERA, alluvial effects in lineament extraction from satellite image are substantially reduced.