• Title/Summary/Keyword: image validation

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A Feature Map Compression Method for Multi-resolution Feature Map with PCA-based Transformation (PCA 기반 변환을 통한 다해상도 피처 맵 압축 방법)

  • Park, Seungjin;Lee, Minhun;Choi, Hansol;Kim, Minsub;Oh, Seoung-Jun;Kim, Younhee;Do, Jihoon;Jeong, Se Yoon;Sim, Donggyu
    • Journal of Broadcast Engineering
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    • v.27 no.1
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    • pp.56-68
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    • 2022
  • In this paper, we propose a compression method for multi-resolution feature maps for VCM. The proposed compression method removes the redundancy between the channels and resolution levels of the multi-resolution feature map through PCA-based transformation. According to each characteristic, the basis vectors and mean vector used for transformation, and the transformation coefficient obtained through the transformation are compressed using a VVC-based coder and DeepCABAC. In order to evaluate performance of the proposed method, the object detection performance was measured for the OpenImageV6 and COCO 2017 validation set, and the BD-rate of MPEG-VCM anchor and feature map compression anchor proposed in this paper was compared using bpp and mAP. As a result of the experiment, the proposed method shows a 25.71% BD-rate performance improvement compared to feature map compression anchor in OpenImageV6. Furthermore, for large objects of the COCO 2017 validation set, the BD-rate performance is improved by up to 43.72% compared to the MPEG-VCM anchor.

In-Orbit Test Operational Validation of the COMS Image Data Acquisition and Control System (천리안 송수신자료전처리시스템의 궤도상 시험 운영 검증)

  • Lim, Hyun-Su;Ahn, Sang-Il;Seo, Seok-Bae;Park, Durk-Jong
    • Journal of Satellite, Information and Communications
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    • v.6 no.2
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    • pp.1-9
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    • 2011
  • The Communication Ocean and Meteorological Satellite(COMS), the first geostationary observation satellite, was successfully launched on June 27th in 2010. The raw data of Meteorological Imager(MI) and Geostationary Ocean Color Imager(GOCI), the main payloads of COMS, is delivered to end-users through the on-ground processing. The COMS Image Data Acquisition and Control System(IDACS) developed by Korea Aerospace Research Institute(KARI) in domestic technologies performs radiometric and geometric corrections to raw data and disseminates pre-processed image data and additional data to end-users through the satellite. Currently the IDACS is in the nominal operations phase after successful in-orbit testing and operates in National Meteorological Satellite Center, Korea Ocean Satellite Center, and Satellite Operations Center, During the in-orbit test period, validations on functionalities and performance IDACS were divided into 1) image data acquisition and transmission, 2) preprocessing of MI and GOCI raw data, and 3) end-user dissemination. This paper presents that IDACS' operational validation results performed during the in-orbit test period after COMS' launch.

Investigation of the Validity of the Image Model for the Analysis of Spherical Wave Reflection

  • Suh, Jin-Sung;Cheung, Wan-Sup
    • The Journal of the Acoustical Society of Korea
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    • v.17 no.3E
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    • pp.27-34
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    • 1998
  • The validity of the image model is investigated both analytically and experimentally in a half space with an infinite single reflecting surface present. This paper exploits the Sommerfeld integral that represents the exact solution for the reflected field in the half space. The solution is shown to be obtained by direct numerical integration which yields more accurate and stable results. The predicted results from the image model are compared to those from the direct numerical integration of the Sommerfeld integral. It is also experimentally demonstrated that the image model gives acceptably accurate results. It is of significance that this paper reveals analytical and experimental validation of using the image model except near-grazing incidence.

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The Analysis on the relation between the Compression Method and the Performance of MSC(Multi-Spectral Camera) Image data

  • Yong, Sang-Soon;Choi, Myung-Jin;Ra, Sung-Woong
    • Proceedings of the KSRS Conference
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    • 2007.10a
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    • pp.530-532
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    • 2007
  • Multi-Spectral Camera(MSC) is a main payload on the KOMPSAT-2 satellite to perform the earth remote sensing. The MSC instrument has one(1) channel for panchromatic imaging and four(4) channel for multi-spectral imaging covering the spectral range from 450nm to 900nm using TDI CCD Focal Plane Array (FPA). The compression method on KOMPSAT-2 MSC was selected and used to match EOS input rate and PDTS output data rate on MSC image data chain. At once the MSC performance was carefully handled to minimize any degradation so that it was analyzed and restored in KGS(KOMPSAT Ground Station) during LEOP and Cal./Val.(Calibration and Validation) phase. In this paper, on-orbit image data chain in MSC and image data processing on KGS including general MSC description is briefly described. The influences on image performance between on-board compression algorithms and between performance restoration methods in ground station are analyzed and discussed.

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COMPONENT-BASED ARCHITECTURE DESIGN FOR EAST INTEROPERABILITY IN SATELLITE IMAGE PROCESSING

  • Yoon, Chang-Pak;Kim, Kyung-Ok;Yang, Young-Kyu
    • Proceedings of the KSRS Conference
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    • 2002.10a
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    • pp.45-48
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    • 2002
  • Satellite image processing software should be able to support interoperability that is to enable consumers, citizens, large and small businesses and governments to make the fullest possible use of the world's spatial data and spatial processing resources. The goal of interoperability is to perform hands-on research, development, testing, fielding, and validation of potential and existing interoperable geoprocessing technologies. In this paper, component based architecture for fast interoperability is designed to maximize interoperability among the OpenGIS components specified in the OpenGIS abstract specifications and implementation specifications and to mix up the OpenGIS components and the fast access mechanism for high performance.

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Prediction of Tumor Progression During Neoadjuvant Chemotherapy and Survival Outcome in Patients With Triple-Negative Breast Cancer

  • Heera Yoen;Soo-Yeon Kim;Dae-Won Lee;Han-Byoel Lee;Nariya Cho
    • Korean Journal of Radiology
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    • v.24 no.7
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    • pp.626-639
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    • 2023
  • Objective: To investigate the association of clinical, pathologic, and magnetic resonance imaging (MRI) variables with progressive disease (PD) during neoadjuvant chemotherapy (NAC) and distant metastasis-free survival (DMFS) in patients with triple-negative breast cancer (TNBC). Materials and Methods: This single-center retrospective study included 252 women with TNBC who underwent NAC between 2010 and 2019. Clinical, pathologic, and treatment data were collected. Two radiologists analyzed the pre-NAC MRI. After random allocation to the development and validation sets in a 2:1 ratio, we developed models to predict PD and DMFS using logistic regression and Cox proportional hazard regression, respectively, and validated them. Results: Among the 252 patients (age, 48.3 ± 10.7 years; 168 in the development set; 84 in the validation set), PD was occurred in 17 patients and 9 patients in the development and validation sets, respectively. In the clinical-pathologic-MRI model, the metaplastic histology (odds ratio [OR], 8.0; P = 0.032), Ki-67 index (OR, 1.02; P = 0.044), and subcutaneous edema (OR, 30.6; P = 0.004) were independently associated with PD in the development set. The clinical-pathologic-MRI model showed a higher area under the receiver-operating characteristic curve (AUC) than the clinical-pathologic model (AUC: 0.69 vs. 0.54; P = 0.017) for predicting PD in the validation set. Distant metastases occurred in 49 patients and 18 patients in the development and validation sets, respectively. Residual disease in both the breast and lymph nodes (hazard ratio [HR], 6.0; P = 0.005) and the presence of lymphovascular invasion (HR, 3.3; P < 0.001) were independently associated with DMFS. The model consisting of these pathologic variables showed a Harrell's C-index of 0.86 in the validation set. Conclusion: The clinical-pathologic-MRI model, which considered subcutaneous edema observed using MRI, performed better than the clinical-pathologic model for predicting PD. However, MRI did not independently contribute to the prediction of DMFS.

Application of Remote Sensing Technique to Enhance the Water Quality Model Validation in a Large Water Body (원격탐사를 이용한 대형 수체의 수질 모델 검증 효과 제고 방안에 관한 연구)

  • Lim, Hyun-Ju;Choi, Jung-Hyun;Park, Seok-Soon
    • Journal of Korean Society of Environmental Engineers
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    • v.28 no.4
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    • pp.447-452
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    • 2006
  • The remote sensing technique was applied to enhance the water qualify model validation in a large water body. Since the satellite image usually covers the wide surface area of a large water body, it can compensate for the lark of measured data points required for model calibration and verification. This paper describes the analysis of Landsat FTM+images collected on April 29th and September 4th in year 2000 to evaluate surface water temperature of Lake Paldang. The water temperature data obtained from the satellite image were compared with model results by estimating three different methods of error criteria. The residual ratios on April 29th and September 4th were 0.13 and 0.04 respectively. This showed that the model result accords with the data obtained from the process of satellite image. Without considering atmospheric interference, however, transformation process of satellite image causes relatively large residual ratio in the surface water temperature distribution pattern on April 29th. In the future study, therefore, the atmospheric properties of image acquisition point needs to be considered for the application of radiance transformation model.

Measures to improve the DEM using SAR images in the river corridor (합성개구레이더 영상을 이용한 하천내 DEM 개선 방안)

  • Kim, Joo-Hun;Noh, Hui-Seong
    • Journal of Korea Water Resources Association
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    • v.55 no.11
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    • pp.913-922
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    • 2022
  • The purpose of this research is to propose the measurement of improving DEM by using the water surface range of SAR image analysis for river corridors and to suggest the construction of satellite-based 3D river spatial information of inaccessible regions such as North Korea. For this research, it has been progressed from the accessible area, watershed of Namgang river, the branch of Nakdonggang river. The satellite image was collected from SAR satellite image data for a year in 2021 which was provided by ESA from Sentinel-1A/B data and extracted from the seasonal water surface area. Ground gauge water level was collected from hourly intervals data by WAMIS. The DEM was improved by analysis of the river altitude of water surface area change by the combination of the ground water level of minimum to maximum water surface area data extracted from SAR image analysis. After the improvement of DEM, the altitude of the river varied that it is defined to comprise more natural form of river DEM than the existing DEM. The correction validation of improvement DEM was necessary in field survey elevation data; however, the correction validation was not progressed due to the absence of the data. Although, the purpose of this research is to provide the improvement of DEM by using the analyzed water surface by existing DEM data and SAR image analysis. After the progression of additional correction validation research, we would plan to examine the application in other places and to progress the additional methodological research to apply in inaccessible and unmeasured area including the North Korea.

Development and Validation of AI Image Segmentation Model for CT Image-Based Sarcopenia Diagnosis (CT 영상 기반 근감소증 진단을 위한 AI 영상분할 모델 개발 및 검증)

  • Lee Chung-Sub;Lim Dong-Wook;Noh Si-Hyeong;Kim Tae-Hoon;Ko Yousun;Kim Kyung Won;Jeong Chang-Won
    • KIPS Transactions on Computer and Communication Systems
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    • v.12 no.3
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    • pp.119-126
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    • 2023
  • Sarcopenia is not well known enough to be classified as a disease in 2021 in Korea, but it is recognized as a social problem in developed countries that have entered an aging society. The diagnosis of sarcopenia follows the international standard guidelines presented by the European Working Group for Sarcopenia in Older People (EWGSOP) and the d Asian Working Group for Sarcopenia (AWGS). Recently, it is recommended to evaluate muscle function by using physical performance evaluation, walking speed measurement, and standing test in addition to absolute muscle mass as a diagnostic method. As a representative method for measuring muscle mass, the body composition analysis method using DEXA has been formally implemented in clinical practice. In addition, various studies for measuring muscle mass using abdominal images of MRI or CT are being actively conducted. In this paper, we develop an AI image segmentation model based on abdominal images of CT with a relatively short imaging time for the diagnosis of sarcopenia and describe the multicenter validation. We developed an artificial intelligence model using U-Net that can automatically segment muscle, subcutaneous fat, and visceral fat by selecting the L3 region from the CT image. Also, to evaluate the performance of the model, internal verification was performed by calculating the intersection over union (IOU) of the partitioned area, and the results of external verification using data from other hospitals are shown. Based on the verification results, we tried to review and supplement the problems and solutions.

Hardware Accelerated Design on Bag of Words Classification Algorithm

  • Lee, Chang-yong;Lee, Ji-yong;Lee, Yong-hwan
    • Journal of Platform Technology
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    • v.6 no.4
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    • pp.26-33
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    • 2018
  • In this paper, we propose an image retrieval algorithm for real-time processing and design it as hardware. The proposed method is based on the classification of BoWs(Bag of Words) algorithm and proposes an image search algorithm using bit stream. K-fold cross validation is used for the verification of the algorithm. Data is classified into seven classes, each class has seven images and a total of 49 images are tested. The test has two kinds of accuracy measurement and speed measurement. The accuracy of the image classification was 86.2% for the BoWs algorithm and 83.7% the proposed hardware-accelerated software implementation algorithm, and the BoWs algorithm was 2.5% higher. The image retrieval processing speed of BoWs is 7.89s and our algorithm is 1.55s. Our algorithm is 5.09 times faster than BoWs algorithm. The algorithm is largely divided into software and hardware parts. In the software structure, C-language is used. The Scale Invariant Feature Transform algorithm is used to extract feature points that are invariant to size and rotation from the image. Bit streams are generated from the extracted feature point. In the hardware architecture, the proposed image retrieval algorithm is written in Verilog HDL and designed and verified by FPGA and Design Compiler. The generated bit streams are stored, the clustering step is performed, and a searcher image databases or an input image databases are generated and matched. Using the proposed algorithm, we can improve convenience and satisfaction of the user in terms of speed if we search using database matching method which represents each object.