Výsledky vyhledávání - "KWANG JU KIM"

Akademický článek

Efficacy of automated machine learning models and feature engineering for diagnosis of equivocal appendicitis using clinical and computed tomography findings

Autor: Juho An, Il Seok Kim, Kwang-Ju Kim, Ji Hyun Park, Hyuncheol Kang, Hyuk Jung Kim, Young Sik Kim, Jung Hwan Ahn

Publikováno v: Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)

Abstract This study evaluates the diagnostic efficacy of automated machine learning (AutoGluon) with automated feature engineering and selection (autofeat), focusing on clinical manifestations, and a model integrating both clinical manifestations and

Externí odkaz: https://doaj.org/article/29c4f5c53432435ebf181f05261eafc5

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Akademický článek

Deep learning‐based multimodal fusion network for segmentation and classification of breast cancers using B‐mode and elastography ultrasound images

Autor: Sampa Misra, Chiho Yoon, Kwang‐Ju Kim, Ravi Managuli, Richard G. Barr, Jongduk Baek, Chulhong Kim

Publikováno v: Bioengineering & Translational Medicine, Vol 8, Iss 6, Pp n/a-n/a (2023)

Abstract Ultrasonography is one of the key medical imaging modalities for evaluating breast lesions. For differentiating benign from malignant lesions, computer‐aided diagnosis (CAD) systems have greatly assisted radiologists by automatically segme

Externí odkaz: https://doaj.org/article/b7099517239c45e489e9dd97789af096

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Akademický článek

Simulations of low impact development designs using the storm water management model.

Autor: Jiyi Jang, Soobin Kim, Sung Min Cha, JongCheol Pyo, Kwang-Sik Yoon, Hankyu Lee, Yongeun Park, In-Su Jang, Kwang-Ju Kim, Jung-Won Yu, Mi-Seon Kang, Hyan-Su Bae, Sang-Soo Baek, Kyung Hwa Cho

Publikováno v: Environmental Engineering Research; Dec2024, Vol. 29 Issue 6, p1-11, 11p

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Akademický článek

Histological Image Segmentation and Classification Using Entropy-Based Convolutional Module

Autor: Hwa-Rang Kim, Kwang-Ju Kim, Kil-Taek Lim, Doo-Hyun Choi

Publikováno v: IEEE Access, Vol 9, Pp 90964-90976 (2021)

As the powerful performance of deep learning has been proven, many computer vision researchers have applied deep learning methods to their works as a breakthrough that could not be achieved with conventional computer vision algorithms. Particularly i

Externí odkaz: https://doaj.org/article/1d2ca9d6f1da4602948f9eb2acd1a17f

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Akademický článek

Multi-Scale Detector for Accurate Vehicle Detection in Traffic Surveillance Data

Autor: Kwang-Ju Kim, Pyong-Kun Kim, Yun-Su Chung, Doo-Hyun Choi

Publikováno v: IEEE Access, Vol 7, Pp 78311-78319 (2019)

The recent research by deep learning has shown many breakthroughs with high performance that were not achieved with traditional machine learning algorithms. Particularly in the field of object detection, commercial products with high accuracy in the

Externí odkaz: https://doaj.org/article/21c509b1d31b4d09becb6e467f0f1cd1

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