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234 results for “classifier”
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Research ArticleOpen accessIn the abstractImproved Intrusion Detection System to Alleviate Attacks on DNS ServiceHani Mahmoud Al-Mimi, Nesreen Adnan Hamad, Mosleh Mohammad Abualhaj et al.Cybercriminals continuously devise new and more sophisticated ways to attack their targets’ security and cyberattacks are on the rise. One of the earliest and most vulnerable network services is the Domain Name System (DNS), which has had several security issues that have been repeatedly exploited over time. Building a strong Intrusion Detection System (IDS) that guards against unwanted access to … …Journal of Computer Science, Vol. 19, Issue 12 · 9 Nov 2023 · 5,786 accessesView PDFCite
Research ArticleOpen accessIn the abstractHuman Age Predication from Face Images Based on Combining Deep Wavelet Network and Machine Learning AlgorithmsZahraa Salam Abu Ghrban, Nidhal K. EL AbbadiDue to the numerous variances in face appearance, age estimation using facial images is a difficult subject. Many factors can affect the estimation of human age such as race, face post, gender, lifestyle, etc. By considering more factors, the optimum performance may be obtained. In this study, we proposed a method to predict the age of facial images. The proposed … …Journal of Computer Science, Vol. 19, Issue 5 · 5 May 2023 · 5,568 accessesView PDFCite
Research ArticleOpen accessIn the abstractPerformance Evaluation of Machine Learning-Based Algorithms to Predict the Early Childhood Development Among Under Five Children in BangladeshMd. Ismail Hossain, Iqramul Haq, Ashis Talukder et al.In this research, an effort has been made to apply a number of classifiers to predict Early Child Development (ECD) in the context of Bangladesh using the Bangladesh multiple indicator cluster survey, 2019 data set (i.e., to evaluate which sort of algorithm best identifies ECDI). To predict the ECD, nine well-known machine learning algorithms were applied, including Linear Regression (LR), … …Journal of Computer Science, Vol. 19, Issue 5 · 5 May 2023 · 6,838 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeep Regularization Mechanism for Combating Class Imbalance Problem in Intrusion Detection System for Defending DDoS Attack in SDNNarender M, Yuvaraju B NIntegration of deep learning into Intrusion Detection Systems (IDS) for Software Defined Networking (SDN) is an emerging field of research. Most of the datasets used to build IDS are highly imbalanced, especially in the case of DDoS attacks, which account for a larger percentage of malicious samples than normal traffic. As a result of a class imbalance, the classification result … …Journal of Computer Science, Vol. 19, Issue 3 · 24 Feb 2023 · 5,659 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeep Learning Approaches for Brain Tumor Diagnosis using Fused Layer AcceleratorMitrabinda Khuntia, Prabhat Kumar Sahu, Swagatika DeviDeep Convolutional Neural Networks (DCNNs) are an emerging field in biomedical processing. Tumor classification is a key stage in the pathology analysis process, and deep learning algorithms for brain tumor categorization have recently shown promising results. However, these approaches often require more storage and more expensive training procedures to input a large number of training variables. To address this issue, … …Journal of Computer Science, Vol. 19, Issue 2 · 19 Jan 2023 · 5,787 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Backward Regressed Capsule Neural Network for Plant Leaf Disease DetectionJennifer Jepkoech, Benson Kipkemboi Kenduiywo, David Muchangi Mugo, Edna Chebet ToolThis study investigated the introduction ofbackward regression coupled with DenseNet features in a Capsule Neural Network(CapsNet) for plant leaf disease classification. Plant diseases are consideredone of the main factors influencing food production and therefore fast cropdisease detection and recognition are important in enhancing food securityinterventions. CapsNets have successfully been adopted for plant leaf diseaseclassification however, backpropagation of signals to preceding … …Journal of Computer Science, Vol. 18, Issue 9 · 8 Sep 2022 · 5,718 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdverse Drug Reaction Detection Using Latent Semantic AnalysisAhmed Adil Nafea, Nazlia Omar, Mohammed M. AL-AniDetecting Adverse Drug Reactions (ADRs) is one of the important information for determining the view of the patient on one drug. Most studies have investigated the extraction of ADRs from social networks, in which users share their opinion on a particular medication. Some studies have used trigger terms to detect ADRs. Such studies showed remarkable performance in terms of extracting … …Journal of Computer Science, Vol. 17, Issue 10 · 28 Oct 2021 · 7,808 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Hybrid Model of Bidirectional Long-Short Term Memory and CNN for Multivariate Time Series Classification of Remote Sensing DataSawsan Morkos GharghoryClassification of multivariate time series has got massive attention in the last decade. The traditional modeling classifiers are complicated patterns and are incompetent to capture the dependencies of multivariate time series data. To include both of the effective features and the embedded relationships in the multivariate time series, a new hybrid model which incorporates both Convolutional Neural Network (CNN) and … …Journal of Computer Science, Vol. 17, Issue 9 · 29 Sep 2021 · 6,686 accessesView PDFCite
Research ArticleOpen accessIn the abstractSentimental Analysis on Health-Related Information with Improving Model Performance using Machine LearningWael M.S. Yafooz, Abdullah AlsaeediSocial media platforms are extensively used in exchanging and sharing information and user experience, thereby resulting in massive outspread and viewing of personal experiences in many fields of life. Thus, informative health-related videos on YouTube are highly perceptible. Many users tend to procure medical treatments and health-related information from social media particularly from YouTube when searching for chronic illness treatments. … …Journal of Computer Science, Vol. 17, Issue 2 · 22 Feb 2021 · 7,460 accessesView PDFCite
Research ArticleOpen accessIn the abstractPhonocardiogram Classification Based on Machine Learning with Multiple Sound FeaturesKhalid M.O. Nahar, Obaida M. Al-Hazaimeh, Ashraf Abu-Ein, Nasr GharaibehIn this study the heartbeat sound signals were tackled by classifying them into heart disease categories such as normal, artifact, murmur and extrahals in an attempt for early detection of heart defects. Phonocardiogram (i.e., PCG) is used to obtain the digital recording dataset of the heart sounds using an electronic stethoscope or mobile device. Multiple features are extracted from the … …Journal of Computer Science, Vol. 16, Issue 11 · 26 Nov 2020 · 8,259 accessesView PDFCite