Journal of Kufa for Mathematics and Computer最新文献

A Machine Learning Model for Cancer Disease Diagnosis using Gene Expression Data 基于基因表达数据的癌症疾病诊断机器学习模型

Journal of Kufa for Mathematics and Computer Pub Date : 2023-08-31 DOI: 10.31642/jokmc/2018/100227

Suhaam Adnan Abdul kareem, Zena Fouad Rasheed

引用次数: 0

Diabetic Retinopathy Classification Using Swin Transformer with Multi Wavelet 基于Swin变压器的糖尿病视网膜病变多小波分类

Journal of Kufa for Mathematics and Computer Pub Date : 2023-08-31 DOI: 10.31642/jokmc/2018/100225

Rasha Ali Dihin, Ebtesam AlShemmary, Waleed Al-Jawher

{"title":"Diabetic Retinopathy Classification Using Swin Transformer with Multi Wavelet","authors":"Rasha Ali Dihin, Ebtesam AlShemmary, Waleed Al-Jawher","doi":"10.31642/jokmc/2018/100225","DOIUrl":"https://doi.org/10.31642/jokmc/2018/100225","url":null,"abstract":"Diabetic retinopathy (DR) impacts over a third of individuals diagnosed with diabetes and stands as the leading cause of vision loss in working-age adults worldwide. Therefore, the early detection and treatment of DR can play a crucial role in minimizing vision loss. This research paper proposes a novel technique that combines Wavelet and multi-Wavelet transforms with Swin Transformer to automatically identify the progression level of diabetic retinopathy. A notable innovation of this study lies in the implementation of the multi-Wavelet transform for extracting relevant features. By incorporating the resulting images into the Swin Transformer model, a unique approach is introduced during the feature extraction phase. The researchers conducted experiments using the publicly available Kaggle APTOS 2019 dataset, which comprises 3662 images. The achieved training accuracy in the experiments was an impressive 97.78%, with a test accuracy of 97.54%. The highest accuracy observed during training reached 98.09%. In comparison, when applying the multi-Wavelet approach to multiclass classification, the training and validation accuracies were 91.60% and 82.42%, respectively, with a testing accuracy of 82%. These results indicate that the multi-Wavelet approach outperforms alternative methods in the study. The model demonstrated exceptional performance in binary classification tasks, exhibiting high accuracies on both the training and test sets. However, it is important to note that the model's accuracy decreased when employed in multiclass classification, emphasizing the need for further investigation and refinement to handle more diverse classification scenarios.","PeriodicalId":499493,"journal":{"name":"Journal of Kufa for Mathematics and Computer","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136035246","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

Elliptic Curve Scalar Multiplication Operation: a Survey Study 椭圆曲线标量乘法运算:概览研究

Journal of Kufa for Mathematics and Computer Pub Date : 2023-08-31 DOI: 10.31642/jokmc/2018/100226

Ayaat Waleed, Najlae Falah Hameed Al Saffar

引用次数: 0

Condensation to Fractal Shapes Constructing 凝结到分形形状构造

Journal of Kufa for Mathematics and Computer Pub Date : 2023-02-13 DOI: 10.31642/jokmc/2018/060300

Adil Alrammahi

引用次数: 0