• Journal of Biomedical Engineering Research
• /
• v.44 no.2
• /
• pp.118-124
• /
• 2023

Many recent studies have reported that the quality of input learning data was vital to the detection of regions of interest. However, due to a lack of research on the quality of learning data on lesion detetcting using gastroscopy, we aimed to quantify the impact of quality difference in endoscopic images to lesion detection models using Image Quality Assessment (IQA) algorithms. Through IQA methods such as BRISQUE (Blind/Referenceless Image Spatial Quality Evaluation), Laplacian Score, and PSNR (Peak Signal-To-Noise) algorithm on 430 sheets of high quality data (HQD) and 430 sheets of low quality data (PQD), we showed that there were significant differences between high and low quality images in lesion detecting through BRISQUE and Laplacian scores (p<0.05). The PSNR value showed 10.62±1.76 dB on average, illustrating the lower lesion detection performance of PQD than HQD. In addition, F1-Score of HQD showed higher detection performance at 77.42±3.36% while F1-Score of PQD showed 66.82±9.07%. Through this study, we hope to contribute to future gastroscopy lesion detection assistance systems that involve IQA algorithms by emphasizing the importance of using high quality data over lower quality data.

• Journal of Korea Water Resources Association
• /
• v.55 no.12
• /
• pp.1041-1052
• /
• 2022

This study is to estimate the optimal ecological flow and analysis the spatial distribution of fish habitat for Andong dam downstream reach (4,565.7 km²) using PHABSIM (Physical Habiat Simulation System) and River2D. To establish habitat models, the cross-section informations and hydraulic input data were collected uisng the Nakdong river basic plan report. The establishment range of PHABSIM was set up about 410.0 m from Gudam streamflow gauging station (GD) and about 6.0 km including GD for River2D. To select representative fish species and construct HSI (Habitat Suitability Index), the fish survey was performed at Pungji bridge where showed well the physical characteristics of target stream located downstream of GD. As a result of the fish survey, Zacco platypus was showed highly relative abundance resulting in selecting as the representative fish species, and HSI was constructed using physical habitat characteristics of the Zacco platypus. The optimal range of HSI was 0.3~0.5 m/s at the velocity suitability index, 0.4~0.6 m at the depth suitability index, and the substrate was sand to fine gravel. As a result of estimating the optimal ecological flow by applying HSI to PHABSIM, the optimal ecological flow for target stream was 20.0 m³/sec. As a result of analysis two-dimensional spatial analysis of fish habitat using River2D, WUA (Weighted Usable Area) was estimated 107,392.0 m²/1000 m under the ecological flow condition and it showed the fish habitat was secured throughout the target stream compared with Q₃₅₅ condition.

• Journal of Internet Computing and Services
• /
• v.20 no.6
• /
• pp.55-63
• /
• 2019

Recently, the use of real-world image data has been increasing to express realistic virtual environments in various application fields such as education, manufacturing, and construction. In particular, with increasing interest in digital twins like smart cities, realistic 3D urban models are being built using real-world images, such as aerial images. However, the captured aerial image includes shadows from the sun, and the 3D city model including the shadows has a problem of distorting and expressing information to the user. Many studies have been conducted to remove the shadow, but it is recognized as a challenging problem that is still difficult to solve. In this paper, we construct a virtual environment dataset including the height map of buildings using 3D spatial information provided by VWorld, and We propose a new shadow detection method using height map and deep learning. According to the experimental results, We can observed that the shadow detection error rate is reduced when using the height map.

• Journal of Korean Society for Geospatial Information Science
• /
• v.16 no.2
• /
• pp.87-95
• /
• 2008

Ladar (Laser Detection And Ranging, Lidar) is a sensor to acquire precise distances to the surfaces of target region using laser signals, which can be suitably applied to ATD (Automatic Target Detection) for guided missiles or aerial vehicles recently. It provides a range image in which each measured distance is expressed as the brightness of the corresponding pixel. Since the precise 3D models can be generated from the Ladar range image, more robust identification and recognition of the targets can be possible. If we simulate the data of Ladar sensor, we can efficiently use this simulator to design and develop Ladar sensors and systems and to develop the data processing algorithm. The purposes of this study are thus to simulate the signals of a Ladar sensor based on linear frequency modulation and to create range images from the simulated Ladar signals. We first simulated the laser signals of a Ladar using FM chirp modulator and then computed the distances from the sensor to a target using the FFT process of the simulated signals. Finally, we created the range image using the distances set.

• Magazine of the Korean Society of Agricultural Engineers
• /
• v.29 no.2
• /
• pp.53-63
• /
• 1987

Due to their wide range of application, deterministic comprehensive hydrologic models using digital computers have been developed in all countries of the world and researches are being undertaken for their appropriate applications. The aim of this study has been to demonstrate the practical implementation of a physically based distributed hydrologic model, the USDAHL-74 model and to investigate its ability to simulate the long term estimate of water balance quantities in a Korean mountainous watershed. Application of the model to Dochuk watershed indicates the following results. 1.Since the USDAHL-74 model includes all the major components of the hydrologic cycle in agricultural watersheds, thus is comprehnsive, the model seems to have a wide range of application from the fact that simulation results obtained are not only runoff volumes m various time units but their spatial variation as well as even soil moisture within the watershed. 2.An approximate calibration to determine the parameter values in the model using various data obtained from D0chuk shed shows that the simulation error of yearly runoff volume is only 0.6 % and a correlation coefficient between observed daily runoff volume and simulated one is 0.91 in all calibrated period.3.As a verification test of the model, runoff volumes are simulated using 1986 year data without changing the parameter values determined by 1985 year data. The tests show that the USDAHL-74 model is a flexible tool and that realistic production to simulate the long term estimate of runoff in Korean mountainous watershed could be obtained using only a short period of calibration.4. Despite of the encouraging results, there still remain minor problems concerning the practical application of the model to improve the result of simulations. Some of these are the small descrepancies between observed and simulated daily runoff volume appeared in the vicinity of peaks and the recession of1 the daily hydrographs and the model performance for the frozen ground and melting process in the model. 5. Alough the use of parameter with physical significance and the ability to improve calibrations on the basis of physical reasoning represents advantages in the simulation for ungaged watersheds, further researches are needed to use the USDAHL-74 mode to simulate runoff in ungaged watersheds.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.29 no.4D
• /
• pp.443-450
• /
• 2009

Uninterrupted facility - since there is a close relationship between traffic volume, speed and density -, when a ramp traffic flow merges into the main line, will change the traffic speed or density, and the corresponding correlational model equation will be changed. Thus, this study, using time and space-series traffic data on areas under the influence of such a merging, identified sections which changed the correlation between speed and density variables, and examined such changes. As a result, the upstream and merging sections showed the "Underwood"-shaped exponent, and the downstream after passing the merging section showed a straight line "Greenshields" model. The downstream section which changed the correlation between speed and density showed a gradual downstream movement phenomenon within 100 m-500 m from the end of the third lane linking with the ramp, as the traffic approached the inner lanes. Also, the upstream section, merging section, and downstream section involving a change showed heterogeneous traffic flows which, in the speed-density model, have a statistically different free flow speed (constant) and a different ratio of free flow speed to jam density (gradient).

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.38 no.4
• /
• pp.375-382
• /
• 2020

As the 4th Industrial Revolution era in worldwide, interest in autonomous vehicles is increasing. but due to recent safety issues such as pedestrian accidents and car accidents, as a technical model for this, the demand for 3D HD maps (High Definition maps) is increasing in including lanes, road markings, road information, traffic lights and traffic signs etc. However, since some complementary points have been continuously raised according to demand, It is necessary to collect the opinions of institutions and companies utilizing HD maps and to improve HD maps. This study was conducted by utilizing the results of the contest for usability verification of HD Maps hosted by the National Geographic Information Institute and organized by the Spatial Information Industry Promotion Institute. For this study, we researched HD maps' layers and codes for HD maps object usability to improve HD maps, constructed HD maps object usability items accordingly, and contested usability verification of HD maps according to the items The contestants conducted verification and analyzed the results. As a result, the most frequently used code for each layer was the flat intersection, and the code showing the highest usage rate was a safety sign. In addition, the use rate of the sub-section and height obstacles was 16.67% and 8.88%, respectively, showing a low ratio. In order to utilize HD maps in the future, this study is expected to require research to continuously collect opinions from customers and improve data objects and data models that are actually needed by customers.

• Korean Journal of Remote Sensing
• /
• v.37 no.5_3
• /
• pp.1405-1423
• /
• 2021

Precipitation is one of the main factors that affect water and energy cycles, and its estimation plays a very important role in securing water resources and timely responding to water disasters. Satellite-based quantitative precipitation estimation (QPE) has the advantage of covering large areas at high spatiotemporal resolution. In this study, machine learning-based rainfall intensity models were developed using Himawari-8 Advanced Himawari Imager (AHI) water vapor channel (6.7 ㎛), infrared channel (10.8 ㎛), and weather radar Column Max (CMAX) composite data based on random forest (RF). The target variables were weather radar reflectivity (dBZ) and rainfall intensity (mm/hr) converted by the Z-R relationship. The results showed that the model which learned CMAX reflectivity produced the Critical Success Index (CSI) of 0.34 and the Mean-Absolute-Error (MAE) of 4.82 mm/hr. When compared to the GeoKompsat-2 and Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN)-Cloud Classification System (CCS) rainfall intensity products, the accuracies improved by 21.73% and 10.81% for CSI, and 31.33% and 23.49% for MAE, respectively. The spatial distribution of the estimated rainfall intensity was much more similar to the radar data than the existing products.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.6 no.3
• /
• pp.170-176
• /
• 2004

This study was carried out to establish a spatial decision support system for evaluating climatic aspects of a given geographic location in complex terrains with respect to the quality apple production. Monthly climate data from S6 synoptic stations across South Korea were collected for 1971-2000. A digital elevation model (DEM) with a 10-m cell spacing was used to spatially interpolate daily maximum and minimum temperatures based on relevant topoclimatological models applied to Jangsoo county in Korea. For daily minimum temperature, a spatial interpolation scheme accommodating the potential influences of cold air accumulation and the temperature inversion was used. For daily maximum temperature estimation, a spatial interpolation model loaded with the overheating index was used. Freezing risk in January was estimated under the recurrence intervals of 30 years. Frost risk at bud-burst and blossom was also estimated. Fruit quality was evaluated for soluble solids, anthocyanin content, Hunter L and A values, and LID ratio, which were expressed as empirical functions of temperature based on long-term field observations. AU themes were prepared as ArcGlS Grids with a 10-m cell spacing. Analysis showed that 11 percent of the whole land area of Jangsoo county might be suitable for quality 'Fuji' apple production. A computer program (MAPLE) was written to help utilize the results in decision-making for site-selection of new orchards in this region.

• Journal of Cadastre & Land InformatiX
• /
• v.47 no.1
• /
• pp.111-126
• /
• 2017

Small-scale UAS(Fusion technique of Unmanned Aerial Vehicles platform and Sensors, 'sUAS') opens various new applications in construction fields and so becoming progressively common due to the considerable potentials in terms of accuracy, costs and abilities. The purpose of this study is that the investigation of the validation on the utilization of sUAS for earth stockpile volume calculations on sites. For this, generate 3D models(DSM) with sUAS aerial images on an cone shaped soil stockpile approximately $270m{\times}300m{\times}20m$, which located at Baegot Life Park in Siheung-si, compared stockpile volume estimates produced by sUAS image analysis, against volume estimates obtained by GNSS Network-RTK ground surveying method which selected as the criteria of earth stockpile volume. The result through comparison and examination show(demonstrate) that there was under 2% difference between the volume calculated with the GNSS Network RTK data and the sUAV data, especially sUAS imaged-based volume estimate of a stockpile can be greatly simplified, done quickly, and very cost effective over conventional terrestrial survey methods. Therefore, with consideration of various plan to assess the height of vegetation, sUAS image-based application expected very useful both volume estimate and 3D geospatial information extraction in small and medium-sized sites.