Sign inSubmit
Tips: “quotes” for a phrase · author:Lee · a DOI goes straight to its article

49 results for “Support Vector Machine method (SVM)”
Set a search alert
Research ArticleOpen accessEvery word in the titleHoax Classification Corona Virus (COVID-19) News in Indonesian using the Support Vector Machine (SVM) MethodWiranto Herry Utomo, Karno Juni PrayogaThe development of information technology more widely, rapidly and quickly provide convenience to the public in access information. Internet is a container or online media makes the information hasn’t been verified or proved to be true which is rapidly spreading in the community. The purpose of this study is to facilitate in determining the hoax news or facts about corona … …Journal of Computer Science, Vol. 17, Issue 8 · 13 Oct 2021 · 6,795 accessesView PDFCite
Research ArticleOpen accessIn the keywordsPecan Weevil Recognition Using Support Vector Machine MethodGhulam Mubashar Hassan, Saleh Mufleh Al-SaqerProblem statement: The Pecan weevil was considered as the most dangerous pest of Pecan fruits. The aim of this research is to evaluate Support Vector Machine method (SVM) for identifying Pecan Weevil among other insects. Eventually, this recognition system will serve in a wireless imaging network for monitoring Pecan Weevils. Approach: SVM has been evaluated using two different kernel functions … …American Journal of Agricultural and Biological Sciences, Vol. 6, Issue 4 · 24 Dec 2011 · 7,926 accessesView PDFCite
Research ArticleOpen accessIn the abstractEpsilon-Insensitive Primal Loss With Support Vector Machine for Robust Cotton Leaf Disease ClassificationPavana Kumar Eramachetty Dhanajayalu, Malathi Sivasamy, Chitveli Siva Balaji YadavCotton diseases significantly reduce both yield and quality of crops, making early and accurate identification of the disease crucial for effective prevention and control. However, achieving a balance between lightweight models and precise classification of cotton diseases remains challenging. This difficulty arises primarily from the dispersed nature of disease symptoms and interference from noisy backgrounds, which complicate the detection process. … …Journal of Computer Science, Vol. 22, Issue 6 · 5 Aug 2026 · 755 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 abstractDefect Classification of Reinforced Concrete Structures with Nondestructive Tests Using Statistical and Machine Learning MethodsSajjad Sayyar-Roudsari, Armaghan Shalbaftabar, Farshid Damirchilo et al.In this study, twelve reinforced concrete beams were constructed, each with specified dimensions and initial compressive strength. The beams were divided into four groups: A control group without any defect, a void group featuring a centrally located void, a corrosion group and a debonding group. The impact echo test was used for nondestructive testing, gathering data on compressive and shear … …American Journal of Engineering and Applied Sciences, Vol. 17, Issue 3 · 11 Jun 2024 · 5,258 accessesView PDFCite
Research ArticleOpen accessIn the abstractA CNN-KNN Based Recognition of Online Handwritten Symbols within Physics Expressions Using Contour-Based Bounding Box (CBBS) Segmentation TechniqueUjwala Kolte, Sachin Naik, Vidya KumbharArtieres, T., Marukatat, S., & Gallinari, P. (2007). Online Handwritten Shape Recognition Using Segmental Hidden Markov Models. IEEE Transactions on Pattern Analysis and Machine Intelligence, 29(2), 205–217. https://doi.org/10.1109/tpami.2007.38 Baró, A., Riba, P., Calvo-Zaragoza, J., & Fornés, A. (2019). From Optical Music Recognition to Handwritten Music Recognition: A baseline. Pattern Recognition Letters, 123, 1–8. https://doi.org/10.1016/j.patrec.2019.02.029 Bresler, M., Prua, D., & Hlavác, … …Journal of Computer Science, Vol. 20, Issue 7 · 7 May 2024 · 6,278 accessesView PDFCite
Research ArticleOpen accessIn the abstractCardiovascular Diseases Identification Using Wavelet Optimization and Modify Cuckoo Search AlgorithmBanit Negi, Abhilekh Bartwal, Agya Ram Verma et al.The problem the author aims to solve is the extraction of discriminatory features in ECG (Electrocardiogram) signals for classification purposes. The scope of the work is to propose a new method for building wavelets that best reflect the discriminatory capacity of ECG signals. The approach involves optimizing the wavelets specifically for the classification function under consideration. To address the problem, … …Journal of Computer Science, Vol. 19, Issue 8 · 3 Aug 2023 · 5,403 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 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 abstractEarly Detection and Classification Approach for Plant Diseases based on MultiScale Image DecompositionAssia Ennouni, Noura Ouled Sihamman, My Abdelouahed Sabri, Abdellah AarabThis paper presents a new and powerful approach for detecting and classifying leaf diseases for plant diagnosis with high accuracy. The main contribution of this paper is that a hybrid approach is proposed by using the combination of Partial Differential Equations (PDE) based image decomposition, segmentation, feature extraction, features selection and classification aiming to improve the classification accuracy and provide … …Journal of Computer Science, Vol. 17, Issue 3 · 25 Mar 2021 · 7,205 accessesView PDFCite