International Journal of Modeling Simulation and Scientific Computing最新文献_第2页

EfficientNets Transfer Learning Strategies for Hispathological Breast Cancer Image Analysis 组织病理乳腺癌图像分析的高效网络迁移学习策略

IF 1.2

International Journal of Modeling Simulation and Scientific Computing Pub Date : 2023-04-05 DOI: 10.1142/s1793962324410095

S. Folorunso, J. B. Awotunde, Y. P. Rangaiah, R. Ogundokun

引用次数: 1

Digital twin-driven robotic arm operation simulation and health management research 数字双驱动机械臂操作仿真与健康管理研究

IF 1.2

International Journal of Modeling Simulation and Scientific Computing Pub Date : 2023-03-30 DOI: 10.1142/s1793962323410337

Guofang Li, Kang Yang, Zhiyu Dong, Xiao-Qiang Ji, Shaopei Wu

引用次数: 0

An Extreme Convolutional Network Model for Brain Disease Prediction Using Smote and Learning Approaches 使用Smote和学习方法预测脑疾病的极端卷积网络模型

IF 1.2

International Journal of Modeling Simulation and Scientific Computing Pub Date : 2023-03-30 DOI: 10.1142/s1793962324410083

N. Ravinder, Moulana Mohammed

引用次数: 0

Modeling and Simulation of Stochastic Transients in Power Systems Based on Frequency Shifting Theory 基于移频理论的电力系统随机暂态建模与仿真

IF 1.2

International Journal of Modeling Simulation and Scientific Computing Pub Date : 2023-03-23 DOI: 10.1142/s1793962324500144

Peng Zhao, Yue Xia, Zhikai You, Yu Hu

引用次数: 0

A Fusified Model for Soft Tissue Prediction Using a Knowledge-Based Deep Learning Approach 基于知识深度学习的软组织预测融合模型

IF 1.2

International Journal of Modeling Simulation and Scientific Computing Pub Date : 2023-03-03 DOI: 10.1142/s1793962324410046

Chandra Sekhar Koppireddy, G. Siva Nageswara Rao

引用次数: 0

Croup Disease Classification Using VGG19 and Resnet 50 Transfer Learning Method 基于VGG19和Resnet 50迁移学习方法的群体疾病分类

IF 1.2

International Journal of Modeling Simulation and Scientific Computing Pub Date : 2023-03-03 DOI: 10.1142/s1793962324410071

E. Vetrimani, M. Aruselvi

{"title":"Croup Disease Classification Using VGG19 and Resnet 50 Transfer Learning Method","authors":"E. Vetrimani, M. Aruselvi","doi":"10.1142/s1793962324410071","DOIUrl":"https://doi.org/10.1142/s1793962324410071","url":null,"abstract":"Detection of any disease in the early stage can save a life. There are many medical imaging modalities like MRI, FMRI, ultrasound, CT, and X-ray used in the detection of disease. In the last decades, neural network-based methods are effective in detecting and classifying the disease based on abnormalities present in the medical images. Acute laryngotracheobronchitis (croup) is one of the common diseases seen in children among the 0.5-3 years age group which infects the respiratory system that can cause the larynx, trachea, and bronchi. Prior detection can lower the risk of spreading and can be treated accurately by a pediatrician. Commonly this infection can be diagnosed though physical examination. But due to the similarity of Covid-19 symptoms urges the physicians to get accurate detection of this disease using X-ray and CT images of the infant's chest and throat. The proposed work aims to develop a croup diagnose system (CDS) which identify the Croup infection through post anterior (PA) view of pediatric X-ray using deep learning algorithm. We used the well-known transfer learning algorithm VGG19 and ResNet50. Data augmentation being adapted for reducing the overfitting and to improve the quantity of image samples. We show that the proposed transfer learning based CDS method can be used to classify the X-ray images into two classes namely, croup and normal. The experiment results confirm that VGG19 performs better than ResNet50 with promising classification accuracy (90.91%.). The results show that the proposed CDS models can be used for more pediatric medical image classification problem. © 2024 World Scientific Publishing Company.","PeriodicalId":45889,"journal":{"name":"International Journal of Modeling Simulation and Scientific Computing","volume":"83 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88803389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Design of a Novel Masking-Based Deep Convolutional Neural Network Approach for Accident Classification 基于掩模的深度卷积神经网络事故分类方法设计

IF 1.2

International Journal of Modeling Simulation and Scientific Computing Pub Date : 2023-03-03 DOI: 10.1142/s179396232441006x

V. Raviteja Kanakala, K. Jagan Mohan, V. Krishna Reddy

引用次数: 0

Design of an Efficient Graph-Based Traversing Method for Establishing Authentication Mechanism in Cloud 一种高效的基于图的云环境下认证机制的遍历方法设计

IF 1.2

International Journal of Modeling Simulation and Scientific Computing Pub Date : 2023-03-03 DOI: 10.1142/s1793962324410058

P. Nagesh, N. Srinivasu

引用次数: 0

Breast Cancer Detection from Histopathological image Dataset Using Hybrid Convolution Neural Network 基于混合卷积神经网络的组织病理图像数据集乳腺癌检测

IF 1.2

International Journal of Modeling Simulation and Scientific Computing Pub Date : 2023-02-18 DOI: 10.1142/s1793962324410034

Nalini Sampath, N. K. Srinath

引用次数: 1

An efficient pure meshless method for phase separation dominated by time fractional Cahn-Hilliard equations 基于时间分数阶Cahn-Hilliard方程的一种高效纯无网格相分离方法

IF 1.2

International Journal of Modeling Simulation and Scientific Computing Pub Date : 2023-02-16 DOI: 10.1142/s1793962324500120

Weiwei Guo, Yujie Zhen, Tao Jiang

引用次数: 0