Research ArticleOpen accessIn the abstractFusing CNN Models for Improved Parkinson’s Disease Detection from Handwritten FeaturesSabrina Benredjem, Tahar MekhazniaNeurodegenerative Diseases (NGD) are a group of progressive neurological disorders, including cognitive decline as Alzheimer’s Disease (AD) and Parkinson’s Disease (PD) that result in the progressive loss of neuronal structure or function. This can lead to a variety of symptoms, in this study we are interested in PD one of the neurological diseases that causes the loss of dopamine-producing neurons … …Journal of Computer Science, Vol. 21, Issue 2 · 22 Jan 2025 · 6,306 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Deep Ensemble Framework for DDoS Attack Recognition and Mitigation in Cloud SDN EnvironmentS. Annie Christila, R. SivakumarMuch research has been done in the recent past on the absolute shift of Internet infrastructure in order to make it more significantly programmable, configurable and make it more conveniently feasible. Software Defined Networking (SDN) forms the basis for this absolute shift in Internet infrastructure. When you look at the benefits of an SDN-based cloud environment they are monumental. Namely, … …Journal of Computer Science, Vol. 20, Issue 10 · 5 Aug 2024 · 5,337 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Comparative Analysis of Smote and CSSF Techniques for Diabetes Classification Using Imbalanced DataBashar Hamad Aubaidan, Rabiah Abdul Kadir, Mohamad Taha IjabDiabetes, a prevalent chronic metabolic disorder, poses a significant burden on healthcare systems worldwide. Accurate and timely diagnosis is crucial for effective management and complication prevention. Machine learning presents a promising solution but often faces challenges due to class imbalance within datasets, particularly the underrepresentation of diabetic cases. To address this issue, we introduce Cluster-based Synthetic Sample Filtering (CSSF), a … …Journal of Computer Science, Vol. 20, Issue 9 · 22 Jul 2024 · 4,998 accessesView PDFCite
Research ArticleOpen accessIn the abstractAI-Guided Anatomical Landmark and Abnormality Detection for Autonomous Endoscopy ExaminationMd Shakhawat Hossain, Munim Ahmed et al.Aabakken, L., Barkun, A. N., Cotton, P. B., Fedorov, E., Fujino, M. A., Ivanova, E., Kudo, S., Kuznetzov, K., De Lange, T., Matsuda, K., Moine, O., Rembacken, B., Rey, J., Romagnuolo, J., Rösch, T., Sawhney, M., Yao, K., & Waye, J. D. (2014). Standardized endoscopic reporting. Journal of Gastroenterology and Hepatology, 29(2), 234–240. https://doi.org/10.1111/jgh.12489 Aliyi, S., Dese, K., & Raj, … …Journal of Computer Science, Vol. 20, Issue 8 · 29 May 2024 · 6,783 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeep Transfer Learning Approach for Student Attendance System During the COVID-19 PandemicSlimane Ennajar, Walid BouarifiMarking students' attendance has been a challenge during the COVID-19 pandemic. It is a time-consuming task due to the abnormally high number of students present during a learning session; many studies have been proposed to improve the system. However, there are still issues with each of these systems; we have employed deep transfer learning techniques using six pre-trained convolutional neural … …Journal of Computer Science, Vol. 20, Issue 3 · 16 Jan 2024 · 6,010 accessesView PDFCite
Research ArticleOpen accessIn the abstractLT-LBP-Based Spatial Texture Feature Extraction with Deep Learning for X-Ray ImagesPankaja Lakshmi P., Sivagami M.The novel logarithmic transformation of Local Binary Pattern (LT-LBP) for texture feature extraction is used with Deep Learning (DL) models. The Computational complexity in the DL models asymptotically increases with the data sesssst and the depth of the layers in Convolutional Neural Networks (CNN). Pre-processing the images before training the DL model holds a strong impact on the operation speed … …Journal of Computer Science, Vol. 20, Issue 1 · 18 Dec 2023 · 7,190 accessesView PDFCite
Research ArticleOpen accessIn the abstractRF-CNNS: Thin Deep Learning Networks For Accelerating Traffic Signs RecognitionBtissam Bousarhane, Driss BouzidiRoad scene analysis is a wide domain of research that aims to ameliorate the environmental perception in intelligent transportation systems, including autonomous vehicles and advanced driver-assistance systems. It also plays a crucial role in road safety improvement, by contributing to the reduction of traffic accidents' rate. Ensuring an efficient recognition of traffic signs contributes enormously to making cars safer, which … …Journal of Computer Science, Vol. 19, Issue 10 · 18 Sep 2023 · 5,335 accessesView PDFCite
Review ArticleOpen accessIn the abstractA Comprehensive Overview of Handwritten Recognition Techniques: A SurveySardar Hasen Ali, Maiwan Bahjat AbdulrazzaqDeep learning and deep neural networks, particularly Convolutional Neural Networks (CNNs), are rapidly growing areas of machine learning and are currently the primary tools used for image analysis and classification applications. Handwriting recognition involves using computer algorithms and software to interpret and recognize handwritten text and drawings and has various applications such as automated handwriting analysis, document digitization, and handwriting-based … …Journal of Computer Science, Vol. 19, Issue 5 · 8 Apr 2023 · 8,763 accessesView PDFCite