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215 articles for “A Hybrid Model”
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Research ArticleOpen accessIn the abstractUnbalance Quantitative Structure Activity Relationship Problem Reduction in Drug DesignD. Pugazhenthi, S. P. RajagopalanProblem statement: Activities of drug molecules can be predicted by Quantitative Structure Activity Relationship (QSAR) models, which overcome the disadvantage of high cost and long cycle by employing traditional experimental methods. With the fact that number of drug molecules with positive activity is rather fewer than that with negatives, it is important to predict molecular activities considering such an unbalanced … …Journal of Computer Science, Vol. 5, Issue 10 · 31 Oct 2009 · 6,707 accessesView PDFCite
Research ArticleOpen accessIn the abstractE-Learning under WebCTZ. A. Al-Khanjari, N. S. Kutti, H. A. RamadhanWith the introduction of Web-Based Instruction (WBI) the traditional classroom-based higher education could be made more effective form of instruction. But the studies have shown the negative results[1]. On the other hand the distance education has derived the direct benefit of WBI through extending classroom instruction in online to reach every remote student. However researchers have identified reasons for the … …Journal of Computer Science, Vol. 1, Issue 4 · 31 Dec 2005 · 6,322 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordOptimized Fractal Fusion Driven Deep Neural Network: An Efficient Hybrid Methodology for Disease Detection and Classification in Plant LeavesDeepkiran Munjal, Mrinal Pandey, Laxman SinghPlant diseases and pest attacks are among the major issues in agriculture, which have a great impact on crop growth and yield. Early and correct detection of these diseases is vital for effective management and keeping plant health at the desired level. This research proposes a new method for detection and classification of plant diseases, the Optimized Fractional Fusion Deep … …Journal of Computer Science, Vol. 21, Issue 12 · 8 Jan 2026 · 2,228 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordTowards an Explainable Approach: Hybrid Residual Network and SVM for Automated Brain Tumor Detection and ClassificationKamini Lamba, Shalli RaniThe abnormal growth of brain cells leads to tumor formation, which can be fatal if not detected and treated promptly. Given the complexity of brain tumors, early detection is critical in healthcare. Traditional radiology-based tumor detection is prone to human error and delays. Hence, a computer- assisted method is needed for accurate and efficient diagnosis. With the rapid advancements in … …Journal of Computer Science, Vol. 22, Issue 1 · 11 Feb 2026 · 1,435 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordAutomated Medical Image Captioning with Soft Attention-Based LSTM Model Utilizing YOLOv4 AlgorithmPaspula Ravinder, Saravanan SrinivasanThe medical image captioning field is one of theprominent fields nowadays. The interpretation and captioning of medical imagescan be a time-consuming and costly process, often requiring expert support. Thegrowing volume of medical images makes it challenging for radiologists tohandle their workload alone. However, addressing the issues of high cost andtime can be achieved by automating the process of medical image … …Journal of Computer Science, Vol. 20, Issue 1 · 16 Dec 2023 · 6,654 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordEnhancing Kidney Stone Detection Accuracy Using Image Processing and a Hybrid Convolutional Deep Belief NetworkGeetha M. N, Barkathulla A, S. Nandhini Devi et al.Automated CKD is a rapidly expanding non-communicable ailment that significantly contributes to global mortality and morbidity. CKD impacts more than 10% of the worldwide population, leading to millions of deaths annually. This paper proposes an enhanced deep learning model for renal disease detection that integrates convolutional and involution layers to enhance classification accuracy. CKD is a worldwide health issue characterised … …Journal of Computer Science, Vol. 22, Issue 10 · 9 Oct 2026 · 774 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordDecoding Discrepancies: Understanding Rating and Review Gaps in Best-Selling ProductsJyoti S Verma, Jaimin N UndaviaClassification of the sentiment and using it for the rating prediction is the major task don in this paper. The emotions and opinions are expressed by the users about a product on the e-commerce website and this provides the basis for the prediction done here. The prediction of the rating enables both the user as well as the seller as … …Journal of Computer Science, Vol. 21, Issue 6 · 29 May 2025 · 5,033 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordA Context Aware Deep Learning Framework for Multi-Level Arabic Fake News Detection Using Hybrid Linguistic RepresentationsNoor Mahmoud Alkudah, Somia Abufakher, Raja Masadeh et al.The rapid spread of false information on social media has made it even more important to be able to spot false news, especially in Arabic-speaking areas where language is more complicated and news is organized in a hierarchy. Recent research show that deep learning and transformer-based models work well, but most of them only look at performance metrics and don't … …Journal of Computer Science, Vol. 22, Issue 3 · 27 Mar 2026 · 1,577 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordA Hybrid Method of Long Short-Term Memory and Auto-Encoder Architectures for Sarcasm DetectionMohammed M. AL-Ani, Nazlia Omar, Ahmed Adil NafeaSarcasm detection is considered one of the most challenging tasks in sentiment analysis and opinion mining applications in the social media. Sarcasm identification is therefore essential for a good public opinion decision. There are some studies on sarcasm detection that apply standard word2vec model and have shown great performance with word-level analysis. However, once a sequence of terms is being … …Journal of Computer Science, Vol. 17, Issue 11 · 1 Dec 2021 · 7,191 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordHuman Iris Recognition Based on Hybrid TechniqueAsaad Noori Hashim, Bushraa Mahdi Al-HashimiIris recognition is a biometric technique that uses iris pattern information to detect person identification. Initially, the system find out the boundary of the pupil and iris. Then, Circular Hough transform used to find out the center of both pupil and iris in order to crop iris part from the eye image. After that, Daugman’s Rubber Sheet model utilized for … …Journal of Computer Science, Vol. 15, Issue 12 · 4 Dec 2019 · 7,807 accessesView PDFCite