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12篇 您的检索式:作者名="Yunja"
    题名 作者 年代 出处 被引量
1Finite element based stress concentration factors for pipes with local wall thinning 显示文摘Kim Yunjae Son Beomgoo 2004International Journal of Pressure Vessels and Piping2004,81,12:1
2Effect of internal pressure on plastic loads of 90° elbows with circumferential part-through surface cracks under in-plane bending显示文摘SeokPyo Hong JongHyun Kim YunJae Kim 0,,:1
3Comparative analysis of 3D body scan measurements and manual measurements of size Korea adult females 显示文摘HAN Hyunsook NAM Yunja CHOI Kyungmi 2010International Journal of Industrial Ergonomics2010,40,5:1
4Measuring the Advertising Efficiency of the Top US Sports Advertisers显示文摘Brown N A Yunjae Cheong Morrison M 2013Journal of Global Scholars of Marketing Science2013,23,1:1
5Compar- ative analysis of 3D body scan measurements and manual measurements of size Korea adult females 显示文摘HAN Hyunsook NAM Yunja CHOI Kyungmi 2010International Journal of Industrial Ergonomics2010,40,5:1
6Compara- tive analysis of 3D body scan measurements and manual measurements of size Korea adult females显示文摘Hyunsook Hana Yunja Nama Kyungmi Choib 2010Interna- tional Journal of Industrial Ergonomics2010,40,:1
7A Decision Criterion for the Optimal Number of Clus- ters in Hierarchical Clustering显示文摘Yunjae Jung Haesun Park Ding-Zhu Du 2003Journal of Global Optimization2003,25,:1
8Comparative analysis of 3D body scan measurements and manual measurements of size Korea adult females 显示文摘HAN Hyunsook NAM Yunja CHOI Kyungmi 2010International Journal of Industrial Ergonomics2010,40,5:1
9A Method for Garment Pattern Generation by Flattening 3D Body Scan Data显示文摘Young Lim Choi Yunja Nam Kueng Mi Choi Ming Hai Cui 0,,:1
10Comparative analysis of 3-D body scan measurementsand manual measurements of size Korea adult females 显示文摘HAN Hyunsook NAM Yunja CHOI Kyungmi 2010International Journal of Industrial Ergonomics2010,40,5:1
11Effect of struc-tural geometry and crack location on crack driving forces for cracksin welds显示文摘Oh Chang Kyun Kim Yunjae Park Jinmoo 2007Engineering Fracture Mechanics2007,74,6:1
12Malaria Blood Smear Classification Using Deep Learning and Best Features Selection显示文摘Malaria is a critical health condition that affects both sultry and frigid region worldwide,giving rise to millions of cases of disease and thousands of deaths over the years.Malaria is caused by parasites that enter the human red blood cells,grow there,and damage them over time.Therefore,it is diagnosed by a detailed examination of blood cells under the microscope.This is the most extensively used malaria diagnosis technique,but it yields limited and unreliable results due to the manual human involvement.In this work,an automated malaria blood smear classification model is proposed,which takes images of both infected and healthy cells and preprocesses themin the L^(*)a^(*)b^(*)color space by employing several contrast enhancement methods.Feature extraction is performed using two pretrained deep convolutional neural networks,DarkNet-53 and DenseNet-201.The features are subsequently agglutinated to be optimized through a nature-based feature reduction method called the whale optimization algorithm.Several classifiers are effectuated on the reduced features,and the achieved results excel in both accuracy and time compared to previously proposed methods.Talha Imran Muhammad Attique Khan Muhammad Sharif Usman Tariq Yu-Dong Zhang Yunyoung Nam Yunja Nam Byeong-Gwon Kang 2022Computers, Materials & Continua2022,,1:0
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